# CoNLL

??? abstract "TLDR"

    ```{ .python .no-check }

    import edsnlp

    stream = edsnlp.data.read_conll(path)

    stream = stream.map_pipeline(nlp)

    ```

You can easily integrate CoNLL formatted files into your project by using EDS-NLP's CoNLL reader.

There are many CoNLL formats corresponding to different shared tasks, but one of the most common is the CoNLL-U format, which is used for dependency parsing. In CoNLL files, each line corresponds to a token and contains various columns with information about the token, such as its index, form, lemma, POS tag, and dependency relation.

EDS-NLP lets you specify the name of the `columns` if they are different from the default CoNLL-U format. If the `columns` parameter is unset, the reader looks for a comment containing `# global.columns` to infer the column names. Otherwise, the columns are

```

ID, FORM, LEMMA, UPOS, XPOS, FEATS, HEAD, DEPREL, DEPS, MISC

```

A typical CoNLL file looks like this:

```{ title="sample.conllu" }

1   euh euh INTJ    _   _   5   discourse   _   SpaceAfter=No

2   ,   ,   PUNCT   _   _   1   punct   _   _

3   il  lui PRON    _   Gender=Masc|Number=Sing|Person=3|PronType=Prs   5   expl:subj   _   _

...

```

## Reading CoNLL files {: #edsnlp.data.conll.read_conll }

::: edsnlp.data.conll.read_conll

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