seqscore 0.3.1

SeqScore: Scoring for named entity recognition and other sequence labeling tasks

SeqScore

SeqScore provides scoring for named entity recognition and other chunking tasks evaluated over sequence labels.

Installation

To install the latest official release of SeqScore, run: pip install seqscore

This will install the package and add the command seqscore in your Python environment.

Usage

Overview

For a list of commands, run seqscore --help:

$ seqscore --help
Usage: seqscore [OPTIONS] COMMAND [ARGS]...

Options:
  --help  Show this message and exit.

Commands:
  convert
  count
  repair
  score
  validate

Scoring

The most common application of SeqScore is scoring CoNLL-format NER predictions. Let's assume you have two files, one containing the correct labels (annotation) and the other containing the predictions (system output).

The correct labels are in the file reference.bio:

This O
is O
a O
sentence O
. O

University B-ORG
of I-ORG
Pennsylvania I-ORG
is O
in O
West B-LOC
Philadelphia I-LOC
, O
Pennsylvania B-LOC
. O

The predictions are in the file predicted.bio:

This O
is O
a O
sentence O
. O

University B-ORG
of I-ORG
Pennsylvania I-ORG
is O
in O
West B-LOC
Philadelphia B-LOC
, O
Pennsylvania B-LOC
. O

To score the predictions, run: seqscore score --labels BIO --reference reference.bio predicted.bio

| Type   |   Precision |   Recall |     F1 |   Reference |   Predicted |   Correct |
|--------|-------------|----------|--------|-------------|-------------|-----------|
| ALL    |       50.00 |    66.67 |  57.14 |           3 |           4 |         2 |
| LOC    |       33.33 |    50.00 |  40.00 |           2 |           3 |         1 |
| ORG    |      100.00 |   100.00 | 100.00 |           1 |           1 |         1 |

A few things to note:

• The reference file must be specifed with the --reference flag.
• The chunk encoding (BIO, BIOES, etc.) must be specified using the --labels flag.
• Both files need to use the same chunk encoding. If you have files that use different chunk encodings, use the convert command
• You can get output in a different format using the --score-format flag

The above scoring command will work for files that do not have any invalid transitions, that is, those that perfectly follow what the encoding allows. However, consider this BIO-encoded file, which we'll call invalid.bio:

This O
is O
a O
sentence O
. O

University I-ORG
of I-ORG
Pennsylvania I-ORG
is O
in O
West B-LOC
Philadelphia I-LOC
, O
Pennsylvania B-LOC
. O

Note that the token University has the label I-ORG, but there is no preceding B-ORG. If we try to score it as before with seqscore score --labels BIO --reference reference.bio invalid.bio, scoring will fail with an error:

seqscore.encoding.EncodingError: Stopping due to validation errors in invalid.bio:
Invalid transition 'O' -> 'I-ORG' for token 'University' on line 7

To score output with invalid transitions, we need to specify a repair method which can correct them. We can tell SeqScore to use the same approach that conlleval uses (which we refer to as "begin" repair in our paper): seqscore score --labels BIO --repair-method conlleval --reference reference.bio invalid.bio

Validation errors in sequence at line 7 of invalid.bio:
Invalid transition 'O' -> 'I-ORG' for token 'University' on line 7
Used method conlleval to repair:
Old: ('I-ORG', 'I-ORG', 'I-ORG', 'O', 'O', 'B-LOC', 'I-LOC', 'O', 'B-LOC', 'O')
New: ('B-ORG', 'I-ORG', 'I-ORG', 'O', 'O', 'B-LOC', 'I-LOC', 'O', 'B-LOC', 'O')
| Type   |   Precision |   Recall |     F1 |   Reference |   Predicted |   Correct |
|--------|-------------|----------|--------|-------------|-------------|-----------|
| ALL    |      100.00 |   100.00 | 100.00 |           3 |           3 |         3 |
| LOC    |      100.00 |   100.00 | 100.00 |           2 |           2 |         2 |
| ORG    |      100.00 |   100.00 | 100.00 |           1 |           1 |         1 |

You can use the -q flag to suppress the logging of all of the repairs applied. You may want to also explore the discard repair, which can produce higher scores for output from models without a CRF or constrained decoding as they are more likely to produce invalid transitions.

Other commands

Other commands are still being documented, but here is a quick summary:

• repair: Apply a repair method to a file, creating an output file with only valid transitions.
• convert: Convert a file from one encoding to another.
• count: Output counts of chunks in the input file.
• validate: Check whether a file has any invalid transitions.

FAQ

Why can't I score output files that are in the format conlleval expects?

At this time, SeqScore intentionally does not support the "merged" format used by conlleval where each line contains a token, correct tag, and predicted tag:

University B-ORG B-ORG
of I-ORG I-ORG
Pennsylvania I-ORG I-ORG
is O O
in O O
West B-LOC B-LOC
Philadelphia I-LOC B-LOC
, O O
Pennsylvania B-LOC B-LOC
. O O

We do not support this format because we have found that creating predictions in this format is a common source of errors in scoring pipelines.

Features coming soon!

• More documentation
• More error analysis tools

Citation

If you use SeqScore, please cite SeqScore: Addressing Barriers to Reproducible Named Entity Recognition Evaluation.

BibTeX:

@inproceedings{palen-michel-etal-2021-seqscore,
    title = "{S}eq{S}core: Addressing Barriers to Reproducible Named Entity Recognition Evaluation",
    author = "Palen-Michel, Chester  and
      Holley, Nolan  and
      Lignos, Constantine",
    booktitle = "Proceedings of the 2nd Workshop on Evaluation and Comparison of NLP Systems",
    month = nov,
    year = "2021",
    address = "Punta Cana, Dominican Republic",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.eval4nlp-1.5",
    pages = "40--50",
}

License

SeqScore is distributed under the MIT License.

Development

For the latest development version, check out the main branch (stable, but sometimes newer than the version on PyPI), or the dev branch (latest, but less tested).

To install from a clone of this repository, use: pip install -e .

Setting up an environment for development

1. Create an environment: conda create -y -n seqscore python=3.8
2. Activate the environment: conda activate seqscore
3. Install dependencies: pip install -r requirements.txt
4. Install seqscore: pip install -e . x