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| author | CoprDistGit <infra@openeuler.org> | 2023-05-15 08:19:09 +0000 |
|---|---|---|
| committer | CoprDistGit <infra@openeuler.org> | 2023-05-15 08:19:09 +0000 |
| commit | fc303c12d6a1fad300217328e81040b9600ddd3d (patch) | |
| tree | af2315028bbcfd17fdb2b5741e27eab008e507c9 | |
| parent | 9dc726aad8b769d31e8bb1e5e490364070862e0d (diff) | |
automatic import of python-vncorenlp
| -rw-r--r-- | .gitignore | 1 | ||||
| -rw-r--r-- | python-vncorenlp.spec | 1530 | ||||
| -rw-r--r-- | sources | 1 |
3 files changed, 1532 insertions, 0 deletions
@@ -0,0 +1 @@ +/vncorenlp-1.0.3.tar.gz diff --git a/python-vncorenlp.spec b/python-vncorenlp.spec new file mode 100644 index 0000000..8f64a8d --- /dev/null +++ b/python-vncorenlp.spec @@ -0,0 +1,1530 @@ +%global _empty_manifest_terminate_build 0 +Name: python-vncorenlp +Version: 1.0.3 +Release: 1 +Summary: A Python wrapper for VnCoreNLP using a bidirectional communication channel. +License: MIT +URL: https://github.com/dnanhkhoa/python-vncorenlp +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/71/c2/96a60cf75421ecc740829fa920c617b3dd7fa6791e17554e7c6f3e7d7fca/vncorenlp-1.0.3.tar.gz +BuildArch: noarch + + +%description +# python-vncorenlp
+
+[]()
+[]()
+
+A Python wrapper for [VnCoreNLP](https://github.com/vncorenlp/VnCoreNLP) using a bidirectional communication channel.
+
+## Table Of Contents
+
+ * [Prerequisites](#prerequisites)
+ * [Installation](#installation)
+ * [Example Usage](#example-usage)
+ * [Use An Existing Server](#use-an-existing-server)
+ * [Debug](#debug)
+ * [Some Use Cases](#some-use-cases)
+ * [License](#license)
+
+## Prerequisites
+
+- Java 1.8+ ([JRE](http://www.oracle.com/technetwork/java/javase/downloads/jre8-downloads-2133155.html) or [JDK](http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html))
+- VnCoreNLP ([Github](https://github.com/vncorenlp/VnCoreNLP) or [Download](https://github.com/vncorenlp/VnCoreNLP/archive/master.zip))
+
+## Installation
+
+You can install this package from PyPI using [pip](http://www.pip-installer.org):
+
+```
+$ [sudo] pip install vncorenlp
+```
+
+For Windows users, please ensure that you run the `Command Prompt` with **admin** privileges.
+
+## Example Usage
+
+A simple example of how to use `vncorenlp`:
+
+```python
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+import logging
+
+from vncorenlp import VnCoreNLP
+
+
+def simple_usage():
+ # Uncomment this line for debugging
+ # logging.basicConfig(level=logging.DEBUG)
+
+ vncorenlp_file = r'.../VnCoreNLP-1.0.1/VnCoreNLP-1.0.1.jar'
+
+ sentences = 'VTV đồng ý chia sẻ bản quyền World Cup 2018 cho HTV để khai thác. ' \
+ 'Nhưng cả hai nhà đài đều phải chờ sự đồng ý của FIFA mới thực hiện được điều này.'
+
+ # Use "with ... as" to close the server automatically
+ with VnCoreNLP(vncorenlp_file) as vncorenlp:
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+ print('POS Tagging:', vncorenlp.pos_tag(sentences))
+ print('Named-Entity Recognizing:', vncorenlp.ner(sentences))
+ print('Dependency Parsing:', vncorenlp.dep_parse(sentences))
+ print('Annotating:', vncorenlp.annotate(sentences))
+ print('Language:', vncorenlp.detect_language(sentences))
+
+ # In this way, you have to close the server manually by calling close function
+ vncorenlp = VnCoreNLP(vncorenlp_file)
+
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+ print('POS Tagging:', vncorenlp.pos_tag(sentences))
+ print('Named-Entity Recognizing:', vncorenlp.ner(sentences))
+ print('Dependency Parsing:', vncorenlp.dep_parse(sentences))
+ print('Annotating:', vncorenlp.annotate(sentences))
+ print('Language:', vncorenlp.detect_language(sentences))
+
+ # Do not forget to close the server
+ vncorenlp.close()
+
+
+if __name__ == '__main__':
+ simple_usage()
+```
+
+And here is the output:
+
+```
+Tokenizing:
+[
+ ['VTV', 'đồng_ý', 'chia_sẻ', 'bản_quyền', 'World_Cup', '2018', 'cho', 'HTV', 'để', 'khai_thác', '.'],
+ ['Nhưng', 'cả', 'hai', 'nhà', 'đài', 'đều', 'phải', 'chờ', 'sự', 'đồng_ý', 'của', 'FIFA', 'mới', 'thực_hiện', 'được', 'điều', 'này', '.']
+]
+
+
+POS Tagging:
+[
+ [('VTV', 'Ny'), ('đồng_ý', 'V'), ('chia_sẻ', 'V'), ('bản_quyền', 'N'), ('World_Cup', 'N'), ('2018', 'M'), ('cho', 'E'), ('HTV', 'Ny'), ('để', 'E'), ('khai_thác', 'V'), ('.', 'CH')],
+ [('Nhưng', 'C'), ('cả', 'P'), ('hai', 'M'), ('nhà', 'N'), ('đài', 'N'), ('đều', 'R'), ('phải', 'V'), ('chờ', 'V'), ('sự', 'Nc'), ('đồng_ý', 'V'), ('của', 'E'), ('FIFA', 'Np'), ('mới', 'R'), ('thực_hiện', 'V'), ('được', 'R'), ('điều', 'N'), ('này', 'P'), ('.', 'CH')]
+]
+
+
+Named-Entity Recognizing:
+[
+ [('VTV', 'O'), ('đồng_ý', 'O'), ('chia_sẻ', 'O'), ('bản_quyền', 'O'), ('World_Cup', 'O'), ('2018', 'O'), ('cho', 'O'), ('HTV', 'O'), ('để', 'O'), ('khai_thác', 'O'), ('.', 'O')],
+ [('Nhưng', 'O'), ('cả', 'O'), ('hai', 'O'), ('nhà', 'O'), ('đài', 'O'), ('đều', 'O'), ('phải', 'O'), ('chờ', 'O'), ('sự', 'O'), ('đồng_ý', 'O'), ('của', 'O'), ('FIFA', 'B-ORG'), ('mới', 'O'), ('thực_hiện', 'O'), ('được', 'O'), ('điều', 'O'), ('này', 'O'), ('.', 'O')]
+]
+
+
+Dependency Parsing:
+[
+ [('sub', 2, 1), ('root', 0, 2), ('vmod', 2, 3), ('dob', 3, 4), ('nmod', 4, 5), ('det', 5, 6), ('iob', 3, 7), ('pob', 7, 8), ('prp', 3, 9), ('vmod', 9, 10), ('punct', 2, 11)],
+ [('dep', 7, 1), ('nmod', 4, 2), ('det', 4, 3), ('sub', 7, 4), ('nmod', 4, 5), ('adv', 7, 6), ('root', 0, 7), ('vmod', 7, 8), ('dob', 8, 9), ('nmod', 9, 10), ('nmod', 9, 11), ('pob', 11, 12), ('adv', 14, 13), ('vmod', 7, 14), ('adv', 14, 15), ('dob', 14, 16), ('det', 16, 17), ('punct', 7, 18)]
+]
+
+
+Annotating:
+{
+ "sentences": [
+ [
+ {
+ "index": 1,
+ "form": "VTV",
+ "posTag": "Ny",
+ "nerLabel": "O",
+ "head": 2,
+ "depLabel": "sub"
+ },
+ {
+ "index": 2,
+ "form": "đồng_ý",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 0,
+ "depLabel": "root"
+ },
+ {
+ "index": 3,
+ "form": "chia_sẻ",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 2,
+ "depLabel": "vmod"
+ },
+ {
+ "index": 4,
+ "form": "bản_quyền",
+ "posTag": "N",
+ "nerLabel": "O",
+ "head": 3,
+ "depLabel": "dob"
+ },
+ {
+ "index": 5,
+ "form": "World_Cup",
+ "posTag": "N",
+ "nerLabel": "O",
+ "head": 4,
+ "depLabel": "nmod"
+ },
+ {
+ "index": 6,
+ "form": "2018",
+ "posTag": "M",
+ "nerLabel": "O",
+ "head": 5,
+ "depLabel": "det"
+ },
+ {
+ "index": 7,
+ "form": "cho",
+ "posTag": "E",
+ "nerLabel": "O",
+ "head": 3,
+ "depLabel": "iob"
+ },
+ {
+ "index": 8,
+ "form": "HTV",
+ "posTag": "Ny",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "pob"
+ },
+ {
+ "index": 9,
+ "form": "để",
+ "posTag": "E",
+ "nerLabel": "O",
+ "head": 3,
+ "depLabel": "prp"
+ },
+ {
+ "index": 10,
+ "form": "khai_thác",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 9,
+ "depLabel": "vmod"
+ },
+ {
+ "index": 11,
+ "form": ".",
+ "posTag": "CH",
+ "nerLabel": "O",
+ "head": 2,
+ "depLabel": "punct"
+ }
+ ],
+ [
+ {
+ "index": 1,
+ "form": "Nhưng",
+ "posTag": "C",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "dep"
+ },
+ {
+ "index": 2,
+ "form": "cả",
+ "posTag": "P",
+ "nerLabel": "O",
+ "head": 4,
+ "depLabel": "nmod"
+ },
+ {
+ "index": 3,
+ "form": "hai",
+ "posTag": "M",
+ "nerLabel": "O",
+ "head": 4,
+ "depLabel": "det"
+ },
+ {
+ "index": 4,
+ "form": "nhà",
+ "posTag": "N",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "sub"
+ },
+ {
+ "index": 5,
+ "form": "đài",
+ "posTag": "N",
+ "nerLabel": "O",
+ "head": 4,
+ "depLabel": "nmod"
+ },
+ {
+ "index": 6,
+ "form": "đều",
+ "posTag": "R",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "adv"
+ },
+ {
+ "index": 7,
+ "form": "phải",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 0,
+ "depLabel": "root"
+ },
+ {
+ "index": 8,
+ "form": "chờ",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "vmod"
+ },
+ {
+ "index": 9,
+ "form": "sự",
+ "posTag": "Nc",
+ "nerLabel": "O",
+ "head": 8,
+ "depLabel": "dob"
+ },
+ {
+ "index": 10,
+ "form": "đồng_ý",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 9,
+ "depLabel": "nmod"
+ },
+ {
+ "index": 11,
+ "form": "của",
+ "posTag": "E",
+ "nerLabel": "O",
+ "head": 9,
+ "depLabel": "nmod"
+ },
+ {
+ "index": 12,
+ "form": "FIFA",
+ "posTag": "Np",
+ "nerLabel": "B-ORG",
+ "head": 11,
+ "depLabel": "pob"
+ },
+ {
+ "index": 13,
+ "form": "mới",
+ "posTag": "R",
+ "nerLabel": "O",
+ "head": 14,
+ "depLabel": "adv"
+ },
+ {
+ "index": 14,
+ "form": "thực_hiện",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "vmod"
+ },
+ {
+ "index": 15,
+ "form": "được",
+ "posTag": "R",
+ "nerLabel": "O",
+ "head": 14,
+ "depLabel": "adv"
+ },
+ {
+ "index": 16,
+ "form": "điều",
+ "posTag": "N",
+ "nerLabel": "O",
+ "head": 14,
+ "depLabel": "dob"
+ },
+ {
+ "index": 17,
+ "form": "này",
+ "posTag": "P",
+ "nerLabel": "O",
+ "head": 16,
+ "depLabel": "det"
+ },
+ {
+ "index": 18,
+ "form": ".",
+ "posTag": "CH",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "punct"
+ }
+ ]
+ ]
+}
+
+
+Language: vi
+```
+
+## Use An Existing Server
+
+First, you need to start the VnCoreNLPServer using this command:
+
+```
+$ vncorenlp -Xmx2g <VnCoreNLP File> -p 9000 -a "wseg,pos,ner,parse"
+```
+
+The parameter `-Xmx2g` means that the VM can allocate a maximum of 2 GB for the Heap Space.
+
+And then connect to the server using this code:
+
+```python
+# Use the existing server
+with VnCoreNLP(address='http://127.0.0.1', port=9000) as vncorenlp:
+ ...
+```
+
+## Debug
+
+There are 3 ways to enable debugging:
+
+```python
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+import logging
+import sys
+
+from vncorenlp import VnCoreNLP
+
+
+# 1. Use the global logger
+# logging.basicConfig(level=logging.DEBUG)
+
+def simple_usage():
+ vncorenlp_file = r'.../VnCoreNLP-1.0.1/VnCoreNLP-1.0.1.jar'
+
+ sentences = 'VTV đồng ý chia sẻ bản quyền World Cup 2018 cho HTV để khai thác. ' \
+ 'Nhưng cả hai nhà đài đều phải chờ sự đồng ý của FIFA mới thực hiện được điều này.'
+
+ # Use "with ... as" to close the server automatically
+ vncorenlp = VnCoreNLP(vncorenlp_file)
+
+ # 2. Set up the local logger here
+ logger = vncorenlp.logger
+ logger.setLevel(logging.DEBUG)
+ # Add stdout
+ ch = logging.StreamHandler(sys.stdout)
+ ch.setLevel(logging.DEBUG)
+ # Add formatter
+ formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+ ch.setFormatter(formatter)
+ logger.addHandler(ch)
+
+ with vncorenlp:
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+ print('POS Tagging:', vncorenlp.pos_tag(sentences))
+ print('Named-Entity Recognizing:', vncorenlp.ner(sentences))
+ print('Dependency Parsing:', vncorenlp.dep_parse(sentences))
+ print('Annotating:', vncorenlp.annotate(sentences))
+ print('Language:', vncorenlp.detect_language(sentences))
+
+ # In this way, you have to close the server manually by calling close function
+ vncorenlp = VnCoreNLP(vncorenlp_file)
+
+ # 3. Set up the local logger here
+ logger = vncorenlp.logger
+ logger.setLevel(logging.DEBUG)
+ # Add stdout
+ ch = logging.StreamHandler(sys.stdout)
+ ch.setLevel(logging.DEBUG)
+ # Add formatter
+ formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+ ch.setFormatter(formatter)
+ logger.addHandler(ch)
+
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+ print('POS Tagging:', vncorenlp.pos_tag(sentences))
+ print('Named-Entity Recognizing:', vncorenlp.ner(sentences))
+ print('Dependency Parsing:', vncorenlp.dep_parse(sentences))
+ print('Annotating:', vncorenlp.annotate(sentences))
+ print('Language:', vncorenlp.detect_language(sentences))
+
+ # Do not forget to close the server
+ vncorenlp.close()
+
+
+if __name__ == '__main__':
+ simple_usage()
+```
+
+## Some Use Cases
+
+```python
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+import logging
+
+from vncorenlp import VnCoreNLP
+
+logging.basicConfig(level=logging.DEBUG)
+
+
+def simple_usage():
+ vncorenlp_file = r'.../VnCoreNLP-1.0.1/VnCoreNLP-1.0.1.jar'
+
+ sentences = 'VTV đồng ý chia sẻ bản quyền World Cup 2018 cho HTV để khai thác. ' \
+ 'Nhưng cả hai nhà đài đều phải chờ sự đồng ý của FIFA mới thực hiện được điều này.'
+
+ # Use only word segmentation
+ with VnCoreNLP(vncorenlp_file, annotators="wseg") as vncorenlp:
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+
+ # Specify the maximum heap size
+ with VnCoreNLP(vncorenlp_file, annotators="wseg", max_heap_size='-Xmx4g') as vncorenlp:
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+
+ # For debugging
+ with VnCoreNLP(vncorenlp_file, annotators="wseg", max_heap_size='-Xmx4g', quiet=False) as vncorenlp:
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+
+
+if __name__ == '__main__':
+ simple_usage()
+```
+
+## License
+
+MIT
+ + +%package -n python3-vncorenlp +Summary: A Python wrapper for VnCoreNLP using a bidirectional communication channel. +Provides: python-vncorenlp +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-vncorenlp +# python-vncorenlp
+
+[]()
+[]()
+
+A Python wrapper for [VnCoreNLP](https://github.com/vncorenlp/VnCoreNLP) using a bidirectional communication channel.
+
+## Table Of Contents
+
+ * [Prerequisites](#prerequisites)
+ * [Installation](#installation)
+ * [Example Usage](#example-usage)
+ * [Use An Existing Server](#use-an-existing-server)
+ * [Debug](#debug)
+ * [Some Use Cases](#some-use-cases)
+ * [License](#license)
+
+## Prerequisites
+
+- Java 1.8+ ([JRE](http://www.oracle.com/technetwork/java/javase/downloads/jre8-downloads-2133155.html) or [JDK](http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html))
+- VnCoreNLP ([Github](https://github.com/vncorenlp/VnCoreNLP) or [Download](https://github.com/vncorenlp/VnCoreNLP/archive/master.zip))
+
+## Installation
+
+You can install this package from PyPI using [pip](http://www.pip-installer.org):
+
+```
+$ [sudo] pip install vncorenlp
+```
+
+For Windows users, please ensure that you run the `Command Prompt` with **admin** privileges.
+
+## Example Usage
+
+A simple example of how to use `vncorenlp`:
+
+```python
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+import logging
+
+from vncorenlp import VnCoreNLP
+
+
+def simple_usage():
+ # Uncomment this line for debugging
+ # logging.basicConfig(level=logging.DEBUG)
+
+ vncorenlp_file = r'.../VnCoreNLP-1.0.1/VnCoreNLP-1.0.1.jar'
+
+ sentences = 'VTV đồng ý chia sẻ bản quyền World Cup 2018 cho HTV để khai thác. ' \
+ 'Nhưng cả hai nhà đài đều phải chờ sự đồng ý của FIFA mới thực hiện được điều này.'
+
+ # Use "with ... as" to close the server automatically
+ with VnCoreNLP(vncorenlp_file) as vncorenlp:
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+ print('POS Tagging:', vncorenlp.pos_tag(sentences))
+ print('Named-Entity Recognizing:', vncorenlp.ner(sentences))
+ print('Dependency Parsing:', vncorenlp.dep_parse(sentences))
+ print('Annotating:', vncorenlp.annotate(sentences))
+ print('Language:', vncorenlp.detect_language(sentences))
+
+ # In this way, you have to close the server manually by calling close function
+ vncorenlp = VnCoreNLP(vncorenlp_file)
+
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+ print('POS Tagging:', vncorenlp.pos_tag(sentences))
+ print('Named-Entity Recognizing:', vncorenlp.ner(sentences))
+ print('Dependency Parsing:', vncorenlp.dep_parse(sentences))
+ print('Annotating:', vncorenlp.annotate(sentences))
+ print('Language:', vncorenlp.detect_language(sentences))
+
+ # Do not forget to close the server
+ vncorenlp.close()
+
+
+if __name__ == '__main__':
+ simple_usage()
+```
+
+And here is the output:
+
+```
+Tokenizing:
+[
+ ['VTV', 'đồng_ý', 'chia_sẻ', 'bản_quyền', 'World_Cup', '2018', 'cho', 'HTV', 'để', 'khai_thác', '.'],
+ ['Nhưng', 'cả', 'hai', 'nhà', 'đài', 'đều', 'phải', 'chờ', 'sự', 'đồng_ý', 'của', 'FIFA', 'mới', 'thực_hiện', 'được', 'điều', 'này', '.']
+]
+
+
+POS Tagging:
+[
+ [('VTV', 'Ny'), ('đồng_ý', 'V'), ('chia_sẻ', 'V'), ('bản_quyền', 'N'), ('World_Cup', 'N'), ('2018', 'M'), ('cho', 'E'), ('HTV', 'Ny'), ('để', 'E'), ('khai_thác', 'V'), ('.', 'CH')],
+ [('Nhưng', 'C'), ('cả', 'P'), ('hai', 'M'), ('nhà', 'N'), ('đài', 'N'), ('đều', 'R'), ('phải', 'V'), ('chờ', 'V'), ('sự', 'Nc'), ('đồng_ý', 'V'), ('của', 'E'), ('FIFA', 'Np'), ('mới', 'R'), ('thực_hiện', 'V'), ('được', 'R'), ('điều', 'N'), ('này', 'P'), ('.', 'CH')]
+]
+
+
+Named-Entity Recognizing:
+[
+ [('VTV', 'O'), ('đồng_ý', 'O'), ('chia_sẻ', 'O'), ('bản_quyền', 'O'), ('World_Cup', 'O'), ('2018', 'O'), ('cho', 'O'), ('HTV', 'O'), ('để', 'O'), ('khai_thác', 'O'), ('.', 'O')],
+ [('Nhưng', 'O'), ('cả', 'O'), ('hai', 'O'), ('nhà', 'O'), ('đài', 'O'), ('đều', 'O'), ('phải', 'O'), ('chờ', 'O'), ('sự', 'O'), ('đồng_ý', 'O'), ('của', 'O'), ('FIFA', 'B-ORG'), ('mới', 'O'), ('thực_hiện', 'O'), ('được', 'O'), ('điều', 'O'), ('này', 'O'), ('.', 'O')]
+]
+
+
+Dependency Parsing:
+[
+ [('sub', 2, 1), ('root', 0, 2), ('vmod', 2, 3), ('dob', 3, 4), ('nmod', 4, 5), ('det', 5, 6), ('iob', 3, 7), ('pob', 7, 8), ('prp', 3, 9), ('vmod', 9, 10), ('punct', 2, 11)],
+ [('dep', 7, 1), ('nmod', 4, 2), ('det', 4, 3), ('sub', 7, 4), ('nmod', 4, 5), ('adv', 7, 6), ('root', 0, 7), ('vmod', 7, 8), ('dob', 8, 9), ('nmod', 9, 10), ('nmod', 9, 11), ('pob', 11, 12), ('adv', 14, 13), ('vmod', 7, 14), ('adv', 14, 15), ('dob', 14, 16), ('det', 16, 17), ('punct', 7, 18)]
+]
+
+
+Annotating:
+{
+ "sentences": [
+ [
+ {
+ "index": 1,
+ "form": "VTV",
+ "posTag": "Ny",
+ "nerLabel": "O",
+ "head": 2,
+ "depLabel": "sub"
+ },
+ {
+ "index": 2,
+ "form": "đồng_ý",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 0,
+ "depLabel": "root"
+ },
+ {
+ "index": 3,
+ "form": "chia_sẻ",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 2,
+ "depLabel": "vmod"
+ },
+ {
+ "index": 4,
+ "form": "bản_quyền",
+ "posTag": "N",
+ "nerLabel": "O",
+ "head": 3,
+ "depLabel": "dob"
+ },
+ {
+ "index": 5,
+ "form": "World_Cup",
+ "posTag": "N",
+ "nerLabel": "O",
+ "head": 4,
+ "depLabel": "nmod"
+ },
+ {
+ "index": 6,
+ "form": "2018",
+ "posTag": "M",
+ "nerLabel": "O",
+ "head": 5,
+ "depLabel": "det"
+ },
+ {
+ "index": 7,
+ "form": "cho",
+ "posTag": "E",
+ "nerLabel": "O",
+ "head": 3,
+ "depLabel": "iob"
+ },
+ {
+ "index": 8,
+ "form": "HTV",
+ "posTag": "Ny",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "pob"
+ },
+ {
+ "index": 9,
+ "form": "để",
+ "posTag": "E",
+ "nerLabel": "O",
+ "head": 3,
+ "depLabel": "prp"
+ },
+ {
+ "index": 10,
+ "form": "khai_thác",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 9,
+ "depLabel": "vmod"
+ },
+ {
+ "index": 11,
+ "form": ".",
+ "posTag": "CH",
+ "nerLabel": "O",
+ "head": 2,
+ "depLabel": "punct"
+ }
+ ],
+ [
+ {
+ "index": 1,
+ "form": "Nhưng",
+ "posTag": "C",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "dep"
+ },
+ {
+ "index": 2,
+ "form": "cả",
+ "posTag": "P",
+ "nerLabel": "O",
+ "head": 4,
+ "depLabel": "nmod"
+ },
+ {
+ "index": 3,
+ "form": "hai",
+ "posTag": "M",
+ "nerLabel": "O",
+ "head": 4,
+ "depLabel": "det"
+ },
+ {
+ "index": 4,
+ "form": "nhà",
+ "posTag": "N",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "sub"
+ },
+ {
+ "index": 5,
+ "form": "đài",
+ "posTag": "N",
+ "nerLabel": "O",
+ "head": 4,
+ "depLabel": "nmod"
+ },
+ {
+ "index": 6,
+ "form": "đều",
+ "posTag": "R",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "adv"
+ },
+ {
+ "index": 7,
+ "form": "phải",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 0,
+ "depLabel": "root"
+ },
+ {
+ "index": 8,
+ "form": "chờ",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "vmod"
+ },
+ {
+ "index": 9,
+ "form": "sự",
+ "posTag": "Nc",
+ "nerLabel": "O",
+ "head": 8,
+ "depLabel": "dob"
+ },
+ {
+ "index": 10,
+ "form": "đồng_ý",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 9,
+ "depLabel": "nmod"
+ },
+ {
+ "index": 11,
+ "form": "của",
+ "posTag": "E",
+ "nerLabel": "O",
+ "head": 9,
+ "depLabel": "nmod"
+ },
+ {
+ "index": 12,
+ "form": "FIFA",
+ "posTag": "Np",
+ "nerLabel": "B-ORG",
+ "head": 11,
+ "depLabel": "pob"
+ },
+ {
+ "index": 13,
+ "form": "mới",
+ "posTag": "R",
+ "nerLabel": "O",
+ "head": 14,
+ "depLabel": "adv"
+ },
+ {
+ "index": 14,
+ "form": "thực_hiện",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "vmod"
+ },
+ {
+ "index": 15,
+ "form": "được",
+ "posTag": "R",
+ "nerLabel": "O",
+ "head": 14,
+ "depLabel": "adv"
+ },
+ {
+ "index": 16,
+ "form": "điều",
+ "posTag": "N",
+ "nerLabel": "O",
+ "head": 14,
+ "depLabel": "dob"
+ },
+ {
+ "index": 17,
+ "form": "này",
+ "posTag": "P",
+ "nerLabel": "O",
+ "head": 16,
+ "depLabel": "det"
+ },
+ {
+ "index": 18,
+ "form": ".",
+ "posTag": "CH",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "punct"
+ }
+ ]
+ ]
+}
+
+
+Language: vi
+```
+
+## Use An Existing Server
+
+First, you need to start the VnCoreNLPServer using this command:
+
+```
+$ vncorenlp -Xmx2g <VnCoreNLP File> -p 9000 -a "wseg,pos,ner,parse"
+```
+
+The parameter `-Xmx2g` means that the VM can allocate a maximum of 2 GB for the Heap Space.
+
+And then connect to the server using this code:
+
+```python
+# Use the existing server
+with VnCoreNLP(address='http://127.0.0.1', port=9000) as vncorenlp:
+ ...
+```
+
+## Debug
+
+There are 3 ways to enable debugging:
+
+```python
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+import logging
+import sys
+
+from vncorenlp import VnCoreNLP
+
+
+# 1. Use the global logger
+# logging.basicConfig(level=logging.DEBUG)
+
+def simple_usage():
+ vncorenlp_file = r'.../VnCoreNLP-1.0.1/VnCoreNLP-1.0.1.jar'
+
+ sentences = 'VTV đồng ý chia sẻ bản quyền World Cup 2018 cho HTV để khai thác. ' \
+ 'Nhưng cả hai nhà đài đều phải chờ sự đồng ý của FIFA mới thực hiện được điều này.'
+
+ # Use "with ... as" to close the server automatically
+ vncorenlp = VnCoreNLP(vncorenlp_file)
+
+ # 2. Set up the local logger here
+ logger = vncorenlp.logger
+ logger.setLevel(logging.DEBUG)
+ # Add stdout
+ ch = logging.StreamHandler(sys.stdout)
+ ch.setLevel(logging.DEBUG)
+ # Add formatter
+ formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+ ch.setFormatter(formatter)
+ logger.addHandler(ch)
+
+ with vncorenlp:
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+ print('POS Tagging:', vncorenlp.pos_tag(sentences))
+ print('Named-Entity Recognizing:', vncorenlp.ner(sentences))
+ print('Dependency Parsing:', vncorenlp.dep_parse(sentences))
+ print('Annotating:', vncorenlp.annotate(sentences))
+ print('Language:', vncorenlp.detect_language(sentences))
+
+ # In this way, you have to close the server manually by calling close function
+ vncorenlp = VnCoreNLP(vncorenlp_file)
+
+ # 3. Set up the local logger here
+ logger = vncorenlp.logger
+ logger.setLevel(logging.DEBUG)
+ # Add stdout
+ ch = logging.StreamHandler(sys.stdout)
+ ch.setLevel(logging.DEBUG)
+ # Add formatter
+ formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+ ch.setFormatter(formatter)
+ logger.addHandler(ch)
+
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+ print('POS Tagging:', vncorenlp.pos_tag(sentences))
+ print('Named-Entity Recognizing:', vncorenlp.ner(sentences))
+ print('Dependency Parsing:', vncorenlp.dep_parse(sentences))
+ print('Annotating:', vncorenlp.annotate(sentences))
+ print('Language:', vncorenlp.detect_language(sentences))
+
+ # Do not forget to close the server
+ vncorenlp.close()
+
+
+if __name__ == '__main__':
+ simple_usage()
+```
+
+## Some Use Cases
+
+```python
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+import logging
+
+from vncorenlp import VnCoreNLP
+
+logging.basicConfig(level=logging.DEBUG)
+
+
+def simple_usage():
+ vncorenlp_file = r'.../VnCoreNLP-1.0.1/VnCoreNLP-1.0.1.jar'
+
+ sentences = 'VTV đồng ý chia sẻ bản quyền World Cup 2018 cho HTV để khai thác. ' \
+ 'Nhưng cả hai nhà đài đều phải chờ sự đồng ý của FIFA mới thực hiện được điều này.'
+
+ # Use only word segmentation
+ with VnCoreNLP(vncorenlp_file, annotators="wseg") as vncorenlp:
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+
+ # Specify the maximum heap size
+ with VnCoreNLP(vncorenlp_file, annotators="wseg", max_heap_size='-Xmx4g') as vncorenlp:
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+
+ # For debugging
+ with VnCoreNLP(vncorenlp_file, annotators="wseg", max_heap_size='-Xmx4g', quiet=False) as vncorenlp:
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+
+
+if __name__ == '__main__':
+ simple_usage()
+```
+
+## License
+
+MIT
+ + +%package help +Summary: Development documents and examples for vncorenlp +Provides: python3-vncorenlp-doc +%description help +# python-vncorenlp
+
+[]()
+[]()
+
+A Python wrapper for [VnCoreNLP](https://github.com/vncorenlp/VnCoreNLP) using a bidirectional communication channel.
+
+## Table Of Contents
+
+ * [Prerequisites](#prerequisites)
+ * [Installation](#installation)
+ * [Example Usage](#example-usage)
+ * [Use An Existing Server](#use-an-existing-server)
+ * [Debug](#debug)
+ * [Some Use Cases](#some-use-cases)
+ * [License](#license)
+
+## Prerequisites
+
+- Java 1.8+ ([JRE](http://www.oracle.com/technetwork/java/javase/downloads/jre8-downloads-2133155.html) or [JDK](http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html))
+- VnCoreNLP ([Github](https://github.com/vncorenlp/VnCoreNLP) or [Download](https://github.com/vncorenlp/VnCoreNLP/archive/master.zip))
+
+## Installation
+
+You can install this package from PyPI using [pip](http://www.pip-installer.org):
+
+```
+$ [sudo] pip install vncorenlp
+```
+
+For Windows users, please ensure that you run the `Command Prompt` with **admin** privileges.
+
+## Example Usage
+
+A simple example of how to use `vncorenlp`:
+
+```python
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+import logging
+
+from vncorenlp import VnCoreNLP
+
+
+def simple_usage():
+ # Uncomment this line for debugging
+ # logging.basicConfig(level=logging.DEBUG)
+
+ vncorenlp_file = r'.../VnCoreNLP-1.0.1/VnCoreNLP-1.0.1.jar'
+
+ sentences = 'VTV đồng ý chia sẻ bản quyền World Cup 2018 cho HTV để khai thác. ' \
+ 'Nhưng cả hai nhà đài đều phải chờ sự đồng ý của FIFA mới thực hiện được điều này.'
+
+ # Use "with ... as" to close the server automatically
+ with VnCoreNLP(vncorenlp_file) as vncorenlp:
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+ print('POS Tagging:', vncorenlp.pos_tag(sentences))
+ print('Named-Entity Recognizing:', vncorenlp.ner(sentences))
+ print('Dependency Parsing:', vncorenlp.dep_parse(sentences))
+ print('Annotating:', vncorenlp.annotate(sentences))
+ print('Language:', vncorenlp.detect_language(sentences))
+
+ # In this way, you have to close the server manually by calling close function
+ vncorenlp = VnCoreNLP(vncorenlp_file)
+
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+ print('POS Tagging:', vncorenlp.pos_tag(sentences))
+ print('Named-Entity Recognizing:', vncorenlp.ner(sentences))
+ print('Dependency Parsing:', vncorenlp.dep_parse(sentences))
+ print('Annotating:', vncorenlp.annotate(sentences))
+ print('Language:', vncorenlp.detect_language(sentences))
+
+ # Do not forget to close the server
+ vncorenlp.close()
+
+
+if __name__ == '__main__':
+ simple_usage()
+```
+
+And here is the output:
+
+```
+Tokenizing:
+[
+ ['VTV', 'đồng_ý', 'chia_sẻ', 'bản_quyền', 'World_Cup', '2018', 'cho', 'HTV', 'để', 'khai_thác', '.'],
+ ['Nhưng', 'cả', 'hai', 'nhà', 'đài', 'đều', 'phải', 'chờ', 'sự', 'đồng_ý', 'của', 'FIFA', 'mới', 'thực_hiện', 'được', 'điều', 'này', '.']
+]
+
+
+POS Tagging:
+[
+ [('VTV', 'Ny'), ('đồng_ý', 'V'), ('chia_sẻ', 'V'), ('bản_quyền', 'N'), ('World_Cup', 'N'), ('2018', 'M'), ('cho', 'E'), ('HTV', 'Ny'), ('để', 'E'), ('khai_thác', 'V'), ('.', 'CH')],
+ [('Nhưng', 'C'), ('cả', 'P'), ('hai', 'M'), ('nhà', 'N'), ('đài', 'N'), ('đều', 'R'), ('phải', 'V'), ('chờ', 'V'), ('sự', 'Nc'), ('đồng_ý', 'V'), ('của', 'E'), ('FIFA', 'Np'), ('mới', 'R'), ('thực_hiện', 'V'), ('được', 'R'), ('điều', 'N'), ('này', 'P'), ('.', 'CH')]
+]
+
+
+Named-Entity Recognizing:
+[
+ [('VTV', 'O'), ('đồng_ý', 'O'), ('chia_sẻ', 'O'), ('bản_quyền', 'O'), ('World_Cup', 'O'), ('2018', 'O'), ('cho', 'O'), ('HTV', 'O'), ('để', 'O'), ('khai_thác', 'O'), ('.', 'O')],
+ [('Nhưng', 'O'), ('cả', 'O'), ('hai', 'O'), ('nhà', 'O'), ('đài', 'O'), ('đều', 'O'), ('phải', 'O'), ('chờ', 'O'), ('sự', 'O'), ('đồng_ý', 'O'), ('của', 'O'), ('FIFA', 'B-ORG'), ('mới', 'O'), ('thực_hiện', 'O'), ('được', 'O'), ('điều', 'O'), ('này', 'O'), ('.', 'O')]
+]
+
+
+Dependency Parsing:
+[
+ [('sub', 2, 1), ('root', 0, 2), ('vmod', 2, 3), ('dob', 3, 4), ('nmod', 4, 5), ('det', 5, 6), ('iob', 3, 7), ('pob', 7, 8), ('prp', 3, 9), ('vmod', 9, 10), ('punct', 2, 11)],
+ [('dep', 7, 1), ('nmod', 4, 2), ('det', 4, 3), ('sub', 7, 4), ('nmod', 4, 5), ('adv', 7, 6), ('root', 0, 7), ('vmod', 7, 8), ('dob', 8, 9), ('nmod', 9, 10), ('nmod', 9, 11), ('pob', 11, 12), ('adv', 14, 13), ('vmod', 7, 14), ('adv', 14, 15), ('dob', 14, 16), ('det', 16, 17), ('punct', 7, 18)]
+]
+
+
+Annotating:
+{
+ "sentences": [
+ [
+ {
+ "index": 1,
+ "form": "VTV",
+ "posTag": "Ny",
+ "nerLabel": "O",
+ "head": 2,
+ "depLabel": "sub"
+ },
+ {
+ "index": 2,
+ "form": "đồng_ý",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 0,
+ "depLabel": "root"
+ },
+ {
+ "index": 3,
+ "form": "chia_sẻ",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 2,
+ "depLabel": "vmod"
+ },
+ {
+ "index": 4,
+ "form": "bản_quyền",
+ "posTag": "N",
+ "nerLabel": "O",
+ "head": 3,
+ "depLabel": "dob"
+ },
+ {
+ "index": 5,
+ "form": "World_Cup",
+ "posTag": "N",
+ "nerLabel": "O",
+ "head": 4,
+ "depLabel": "nmod"
+ },
+ {
+ "index": 6,
+ "form": "2018",
+ "posTag": "M",
+ "nerLabel": "O",
+ "head": 5,
+ "depLabel": "det"
+ },
+ {
+ "index": 7,
+ "form": "cho",
+ "posTag": "E",
+ "nerLabel": "O",
+ "head": 3,
+ "depLabel": "iob"
+ },
+ {
+ "index": 8,
+ "form": "HTV",
+ "posTag": "Ny",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "pob"
+ },
+ {
+ "index": 9,
+ "form": "để",
+ "posTag": "E",
+ "nerLabel": "O",
+ "head": 3,
+ "depLabel": "prp"
+ },
+ {
+ "index": 10,
+ "form": "khai_thác",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 9,
+ "depLabel": "vmod"
+ },
+ {
+ "index": 11,
+ "form": ".",
+ "posTag": "CH",
+ "nerLabel": "O",
+ "head": 2,
+ "depLabel": "punct"
+ }
+ ],
+ [
+ {
+ "index": 1,
+ "form": "Nhưng",
+ "posTag": "C",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "dep"
+ },
+ {
+ "index": 2,
+ "form": "cả",
+ "posTag": "P",
+ "nerLabel": "O",
+ "head": 4,
+ "depLabel": "nmod"
+ },
+ {
+ "index": 3,
+ "form": "hai",
+ "posTag": "M",
+ "nerLabel": "O",
+ "head": 4,
+ "depLabel": "det"
+ },
+ {
+ "index": 4,
+ "form": "nhà",
+ "posTag": "N",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "sub"
+ },
+ {
+ "index": 5,
+ "form": "đài",
+ "posTag": "N",
+ "nerLabel": "O",
+ "head": 4,
+ "depLabel": "nmod"
+ },
+ {
+ "index": 6,
+ "form": "đều",
+ "posTag": "R",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "adv"
+ },
+ {
+ "index": 7,
+ "form": "phải",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 0,
+ "depLabel": "root"
+ },
+ {
+ "index": 8,
+ "form": "chờ",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "vmod"
+ },
+ {
+ "index": 9,
+ "form": "sự",
+ "posTag": "Nc",
+ "nerLabel": "O",
+ "head": 8,
+ "depLabel": "dob"
+ },
+ {
+ "index": 10,
+ "form": "đồng_ý",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 9,
+ "depLabel": "nmod"
+ },
+ {
+ "index": 11,
+ "form": "của",
+ "posTag": "E",
+ "nerLabel": "O",
+ "head": 9,
+ "depLabel": "nmod"
+ },
+ {
+ "index": 12,
+ "form": "FIFA",
+ "posTag": "Np",
+ "nerLabel": "B-ORG",
+ "head": 11,
+ "depLabel": "pob"
+ },
+ {
+ "index": 13,
+ "form": "mới",
+ "posTag": "R",
+ "nerLabel": "O",
+ "head": 14,
+ "depLabel": "adv"
+ },
+ {
+ "index": 14,
+ "form": "thực_hiện",
+ "posTag": "V",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "vmod"
+ },
+ {
+ "index": 15,
+ "form": "được",
+ "posTag": "R",
+ "nerLabel": "O",
+ "head": 14,
+ "depLabel": "adv"
+ },
+ {
+ "index": 16,
+ "form": "điều",
+ "posTag": "N",
+ "nerLabel": "O",
+ "head": 14,
+ "depLabel": "dob"
+ },
+ {
+ "index": 17,
+ "form": "này",
+ "posTag": "P",
+ "nerLabel": "O",
+ "head": 16,
+ "depLabel": "det"
+ },
+ {
+ "index": 18,
+ "form": ".",
+ "posTag": "CH",
+ "nerLabel": "O",
+ "head": 7,
+ "depLabel": "punct"
+ }
+ ]
+ ]
+}
+
+
+Language: vi
+```
+
+## Use An Existing Server
+
+First, you need to start the VnCoreNLPServer using this command:
+
+```
+$ vncorenlp -Xmx2g <VnCoreNLP File> -p 9000 -a "wseg,pos,ner,parse"
+```
+
+The parameter `-Xmx2g` means that the VM can allocate a maximum of 2 GB for the Heap Space.
+
+And then connect to the server using this code:
+
+```python
+# Use the existing server
+with VnCoreNLP(address='http://127.0.0.1', port=9000) as vncorenlp:
+ ...
+```
+
+## Debug
+
+There are 3 ways to enable debugging:
+
+```python
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+import logging
+import sys
+
+from vncorenlp import VnCoreNLP
+
+
+# 1. Use the global logger
+# logging.basicConfig(level=logging.DEBUG)
+
+def simple_usage():
+ vncorenlp_file = r'.../VnCoreNLP-1.0.1/VnCoreNLP-1.0.1.jar'
+
+ sentences = 'VTV đồng ý chia sẻ bản quyền World Cup 2018 cho HTV để khai thác. ' \
+ 'Nhưng cả hai nhà đài đều phải chờ sự đồng ý của FIFA mới thực hiện được điều này.'
+
+ # Use "with ... as" to close the server automatically
+ vncorenlp = VnCoreNLP(vncorenlp_file)
+
+ # 2. Set up the local logger here
+ logger = vncorenlp.logger
+ logger.setLevel(logging.DEBUG)
+ # Add stdout
+ ch = logging.StreamHandler(sys.stdout)
+ ch.setLevel(logging.DEBUG)
+ # Add formatter
+ formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+ ch.setFormatter(formatter)
+ logger.addHandler(ch)
+
+ with vncorenlp:
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+ print('POS Tagging:', vncorenlp.pos_tag(sentences))
+ print('Named-Entity Recognizing:', vncorenlp.ner(sentences))
+ print('Dependency Parsing:', vncorenlp.dep_parse(sentences))
+ print('Annotating:', vncorenlp.annotate(sentences))
+ print('Language:', vncorenlp.detect_language(sentences))
+
+ # In this way, you have to close the server manually by calling close function
+ vncorenlp = VnCoreNLP(vncorenlp_file)
+
+ # 3. Set up the local logger here
+ logger = vncorenlp.logger
+ logger.setLevel(logging.DEBUG)
+ # Add stdout
+ ch = logging.StreamHandler(sys.stdout)
+ ch.setLevel(logging.DEBUG)
+ # Add formatter
+ formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+ ch.setFormatter(formatter)
+ logger.addHandler(ch)
+
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+ print('POS Tagging:', vncorenlp.pos_tag(sentences))
+ print('Named-Entity Recognizing:', vncorenlp.ner(sentences))
+ print('Dependency Parsing:', vncorenlp.dep_parse(sentences))
+ print('Annotating:', vncorenlp.annotate(sentences))
+ print('Language:', vncorenlp.detect_language(sentences))
+
+ # Do not forget to close the server
+ vncorenlp.close()
+
+
+if __name__ == '__main__':
+ simple_usage()
+```
+
+## Some Use Cases
+
+```python
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+import logging
+
+from vncorenlp import VnCoreNLP
+
+logging.basicConfig(level=logging.DEBUG)
+
+
+def simple_usage():
+ vncorenlp_file = r'.../VnCoreNLP-1.0.1/VnCoreNLP-1.0.1.jar'
+
+ sentences = 'VTV đồng ý chia sẻ bản quyền World Cup 2018 cho HTV để khai thác. ' \
+ 'Nhưng cả hai nhà đài đều phải chờ sự đồng ý của FIFA mới thực hiện được điều này.'
+
+ # Use only word segmentation
+ with VnCoreNLP(vncorenlp_file, annotators="wseg") as vncorenlp:
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+
+ # Specify the maximum heap size
+ with VnCoreNLP(vncorenlp_file, annotators="wseg", max_heap_size='-Xmx4g') as vncorenlp:
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+
+ # For debugging
+ with VnCoreNLP(vncorenlp_file, annotators="wseg", max_heap_size='-Xmx4g', quiet=False) as vncorenlp:
+ print('Tokenizing:', vncorenlp.tokenize(sentences))
+
+
+if __name__ == '__main__':
+ simple_usage()
+```
+
+## License
+
+MIT
+ + +%prep +%autosetup -n vncorenlp-1.0.3 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-vncorenlp -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 1.0.3-1 +- Package Spec generated @@ -0,0 +1 @@ +0e41711b4170458d8f6e9d8c42100250 vncorenlp-1.0.3.tar.gz |