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spaCy/extra/example_data/ner_example_data/ner-sent-per-line.json

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Updates/bugfixes for NER/IOB converters (#4186) * Updates/bugfixes for NER/IOB converters * Converter formats `ner` and `iob` use autodetect to choose a converter if possible * `iob2json` is reverted to handle sentence-per-line data like `word1|pos1|ent1 word2|pos2|ent2` * Fix bug in `merge_sentences()` so the second sentence in each batch isn't skipped * `conll_ner2json` is made more general so it can handle more formats with whitespace-separated columns * Supports all formats where the first column is the token and the final column is the IOB tag; if present, the second column is the POS tag * As in CoNLL 2003 NER, blank lines separate sentences, `-DOCSTART- -X- O O` separates documents * Add option for segmenting sentences (new flag `-s`) * Parser-based sentence segmentation with a provided model, otherwise with sentencizer (new option `-b` to specify model) * Can group sentences into documents with `n_sents` as long as sentence segmentation is available * Only applies automatic segmentation when there are no existing delimiters in the data * Provide info about settings applied during conversion with warnings and suggestions if settings conflict or might not be not optimal. * Add tests for common formats * Add '(default)' back to docs for -c auto * Add document count back to output * Revert changes to converter output message * Use explicit tabs in convert CLI test data * Adjust/add messages for n_sents=1 default * Add sample NER data to training examples * Update README * Add links in docs to example NER data * Define msg within converters
2019-08-29 10:04:01 +00:00
[
{
"id":0,
"paragraphs":[
{
"sentences":[
{
"tokens":[
{
"orth":"When",
"tag":"WRB",
"ner":"O"
},
{
"orth":"Sebastian",
"tag":"NNP",
"ner":"B-PERSON"
},
{
"orth":"Thrun",
"tag":"NNP",
"ner":"L-PERSON"
},
{
"orth":"started",
"tag":"VBD",
"ner":"O"
},
{
"orth":"working",
"tag":"VBG",
"ner":"O"
},
{
"orth":"on",
"tag":"IN",
"ner":"O"
},
{
"orth":"self",
"tag":"NN",
"ner":"O"
},
{
"orth":"-",
"tag":"HYPH",
"ner":"O"
},
{
"orth":"driving",
"tag":"VBG",
"ner":"O"
},
{
"orth":"cars",
"tag":"NNS",
"ner":"O"
},
{
"orth":"at",
"tag":"IN",
"ner":"O"
},
{
"orth":"Google",
"tag":"NNP",
"ner":"U-ORG"
},
{
"orth":"in",
"tag":"IN",
"ner":"O"
},
{
"orth":"2007",
"tag":"CD",
"ner":"U-DATE"
},
{
"orth":",",
"tag":",",
"ner":"O"
},
{
"orth":"few",
"tag":"JJ",
"ner":"O"
},
{
"orth":"people",
"tag":"NNS",
"ner":"O"
},
{
"orth":"outside",
"tag":"RB",
"ner":"O"
},
{
"orth":"of",
"tag":"IN",
"ner":"O"
},
{
"orth":"the",
"tag":"DT",
"ner":"O"
},
{
"orth":"company",
"tag":"NN",
"ner":"O"
},
{
"orth":"took",
"tag":"VBD",
"ner":"O"
},
{
"orth":"him",
"tag":"PRP",
"ner":"O"
},
{
"orth":"seriously",
"tag":"RB",
"ner":"O"
},
{
"orth":".",
"tag":".",
"ner":"O"
}
]
},
{
"tokens":[
{
"orth":"\u201c",
"tag":"''",
"ner":"O"
},
{
"orth":"I",
"tag":"PRP",
"ner":"O"
},
{
"orth":"can",
"tag":"MD",
"ner":"O"
},
{
"orth":"tell",
"tag":"VB",
"ner":"O"
},
{
"orth":"you",
"tag":"PRP",
"ner":"O"
},
{
"orth":"very",
"tag":"RB",
"ner":"O"
},
{
"orth":"senior",
"tag":"JJ",
"ner":"O"
},
{
"orth":"CEOs",
"tag":"NNS",
"ner":"O"
},
{
"orth":"of",
"tag":"IN",
"ner":"O"
},
{
"orth":"major",
"tag":"JJ",
"ner":"O"
},
{
"orth":"American",
"tag":"JJ",
"ner":"U-NORP"
},
{
"orth":"car",
"tag":"NN",
"ner":"O"
},
{
"orth":"companies",
"tag":"NNS",
"ner":"O"
},
{
"orth":"would",
"tag":"MD",
"ner":"O"
},
{
"orth":"shake",
"tag":"VB",
"ner":"O"
},
{
"orth":"my",
"tag":"PRP$",
"ner":"O"
},
{
"orth":"hand",
"tag":"NN",
"ner":"O"
},
{
"orth":"and",
"tag":"CC",
"ner":"O"
},
{
"orth":"turn",
"tag":"VB",
"ner":"O"
},
{
"orth":"away",
"tag":"RB",
"ner":"O"
},
{
"orth":"because",
"tag":"IN",
"ner":"O"
},
{
"orth":"I",
"tag":"PRP",
"ner":"O"
},
{
"orth":"was",
"tag":"VBD",
"ner":"O"
},
{
"orth":"n\u2019t",
"tag":"RB",
"ner":"O"
},
{
"orth":"worth",
"tag":"JJ",
"ner":"O"
},
{
"orth":"talking",
"tag":"VBG",
"ner":"O"
},
{
"orth":"to",
"tag":"IN",
"ner":"O"
},
{
"orth":",",
"tag":",",
"ner":"O"
},
{
"orth":"\u201d",
"tag":"''",
"ner":"O"
},
{
"orth":"said",
"tag":"VBD",
"ner":"O"
},
{
"orth":"Thrun",
"tag":"NNP",
"ner":"U-PERSON"
},
{
"orth":",",
"tag":",",
"ner":"O"
},
{
"orth":"in",
"tag":"IN",
"ner":"O"
},
{
"orth":"an",
"tag":"DT",
"ner":"O"
},
{
"orth":"interview",
"tag":"NN",
"ner":"O"
},
{
"orth":"with",
"tag":"IN",
"ner":"O"
},
{
"orth":"Recode",
"tag":"NNP",
"ner":"U-ORG"
},
{
"orth":"earlier",
"tag":"RBR",
"ner":"B-DATE"
},
{
"orth":"this",
"tag":"DT",
"ner":"I-DATE"
},
{
"orth":"week",
"tag":"NN",
"ner":"L-DATE"
},
{
"orth":".",
"tag":".",
"ner":"O"
}
]
}
]
}
]
}
]