spaCy/examples/training/ner_example_data/ner-token-per-line-with-pos.iob
adrianeboyd 82159b5c19 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 12:04:01 +02:00

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