Metadata-Version: 2.1
Name: jel
Version: 0.1.2
Summary: Japanese Entity Linker.
Home-page: https://github.com/izuna385/jel
Author: izuna385
Author-email: izuna385@gmail.com
License: UNKNOWN
Description: <p align="center"><img width="20%" src="docs/jel-logo.png"></p>
        
        # jel: Japanese Entity Linker
        * jel - Japanese Entity Linker - is Bi-encoder based entity linker for japanese.
        
        # Usage
        * Currently, `link` and `question` methods are supported.
        
        ## `el.link`
        * This returnes named entity and its candidate ones from Wikipedia titles.
        ```python
        from jel import EntityLinker
        el = EntityLinker()
        
        el.link('今日は東京都のマックにアップルを買いに行き、スティーブジョブスとドナルドに会い、堀田区に引っ越した。')
        >> [
            {
                "text": "東京都",
                "label": "GPE",
                "span": [
                    3,
                    6
                ],
                "predicted_normalized_entities": [
                    [
                        "東京都庁",
                        0.1084
                    ],
                    [
                        "東京",
                        0.0633
                    ],
                    [
                        "国家地方警察東京都本部",
                        0.0604
                    ],
                    [
                        "東京都",
                        0.0598
                    ],
                    ...
                ]
            },
            {
                "text": "アップル",
                "label": "ORG",
                "span": [
                    11,
                    15
                ],
                "predicted_normalized_entities": [
                    [
                        "アップル",
                        0.2986
                    ],
                    [
                        "アップル インコーポレイテッド",
                        0.1792
                    ],
                    …
                ]
            }
        ```
        
        ## `el.question`
        * This returnes candidate entity for any question from Wikipedia titles.
        ```python
        >>> linker.question('日本の総理大臣は？')
        [('菅内閣', 0.05791765857101555), ('枢密院', 0.05592481946602986), ('党', 0.05430194711042564), ('総選挙', 0.052795400668513175)]
        ```
        
        ## Setup
        `pip install jel`
        
        ## Test
        `$ python pytest`
        
        ## Notes
        * faiss==1.5.3 from pip causes error _swigfaiss. 
        * To solve this, see [this issue](https://github.com/facebookresearch/faiss/issues/821#issuecomment-573531694).
        
        ## LICENSE
        Apache 2.0 License.
        
        ## CITATION
        ```
        @INPROCEEDINGS{manabe2019chive,
            author    = {真鍋陽俊, 岡照晃, 海川祥毅, 髙岡一馬, 内田佳孝, 浅原正幸},
            title     = {複数粒度の分割結果に基づく日本語単語分散表現},
            booktitle = "言語処理学会第25回年次大会(NLP2019)",
            year      = "2019",
            pages     = "NLP2019-P8-5",
            publisher = "言語処理学会",
        }
        ```
Keywords: jel
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3.7
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
