SeqScore provides scoring for named entity recognition and other chunking tasks evaluated over sequence labels.
SeqScore is maintained by the BLT Lab at Brandeis University. Please open an issue if you find incorrect behavior or features you would like to see added. Due to the risk of introducing regressions or incorrect scoring behavior, we generally do not accept pull requests. Please do not open a pull request unless you are asked to do so by a maintainer in an issue.
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.
SeqScore requires Python 3.10 or higher. It is tested on Python 3.10, 3.11, 3.12, 3.13, and 3.14.
SeqScore is distributed under the MIT License.
If you use SeqScore, please cite SeqScore: Addressing Barriers to Reproducible Named Entity Recognition Evaluation and Improving NER Research Workflows with SeqScore.
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"
}
@inproceedings{lignos-etal-2023-improving,
title = "Improving {NER} Research Workflows with {S}eq{S}core",
author = "Lignos, Constantine and
Kruse, Maya and
Rueda, Andrew",
editor = "Tan, Liling and
Milajevs, Dmitrijs and
Chauhan, Geeticka and
Gwinnup, Jeremy and
Rippeth, Elijah",
booktitle = "Proceedings of the 3rd Workshop for Natural Language Processing Open Source Software (NLP-OSS 2023)",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.nlposs-1.17/",
doi = "10.18653/v1/2023.nlposs-1.17",
pages = "147--152"
}
Other papers related to SeqScore include:
- If You Build Your Own NER Scorer, Non-replicable Results Will Come
- Toward More Meaningful Resources for Lower-resourced Languages
- CoNLL#: Fine-grained Error Analysis and a Corrected Test Set for CoNLL-03 English
For a list of commands, run seqscore --help:
$ seqscore --help
Usage: seqscore [OPTIONS] COMMAND [ARGS]...
Provides scoring and analysis tools for NER/chunking files (version 0.6.0)
Options:
--version Show the version and exit.
--help Show this message and exit.
Commands:
convert convert between mention encodings
count show counts for all the mentions contained in a file
extract-text extract text from a file
process transform entity types by keeping/removing/mapping
repair repair invalid label transitions
score score a file and report performance or an error count table
summarize show counts of the documents, sentences, and entity types
validate validate labels
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 samples/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 samples/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 samples/reference.bio samples/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 specified with the
--referenceflag. - The chunk encoding (BIO, BIOES, etc.) must be specified using the
--labelsflag. - Both files need to use the same chunk encoding. If you have files that use different
chunk encodings, use the
convertcommand. - You can get output in different formats using the
--score-formatflag. Using--score-format delimwill produce tab-delimited output. In the delimited format, you can specify the--full-precisionflag to output higher numerical precision. - In the default (pretty) output format, numbers are rounded "half up" at two decimal
places. In other words, 57.124 will round to 57.12, and 57.125 will round to 57.13.
This is different than the "half even" rounding used by
conllevaland other libraries that rely onprintfbehavior for rounding. Half up rounding is used as it is more likely to match the rounding a user would perform if shown three decimal places. If you requestconllevaloutput format, the same rounding used byconllevalwill be used.
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, samples/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 score it as before with
seqscore score --labels BIO --reference samples/reference.bio samples/invalid.bio,
scoring will fail:
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 samples/reference.bio samples/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. For
example, running the command
seqscore score -q --labels BIO --repair-method conlleval --reference samples/reference.bio samples/invalid.bio
will hide the repairs:
| 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 may want to also explore the discard repair, which can produce higher scores for
output from models without a CRF/constrained decoding as they are more likely to produce
invalid transitions.
SeqScore can also display all errors (false positives and false negatives) encountered
in scoring using the --error-counts flag. For example, running the command
seqscore score --labels BIO --error-counts --reference samples/reference.bio samples/predicted.bio
will produce the following output:
| Count | Error | Type | Tokens |
|---------|---------|--------|-------------------|
| 1 | FP | LOC | Philadelphia |
| 1 | FP | LOC | West |
| 1 | FN | LOC | West Philadelphia |
The output shows that the system produced two false positives and missed one mention in
the reference (false negative). The most frequent errors appear at the top. The
--error-counts flag can be combined with --score-format delim to write a delimited
table that can be read as a spreadsheet.
To check if a file has any invalid transitions, we can run
seqscore validate --labels BIO samples/reference.bio:
No errors found in 0 tokens, 2 sequences, and 1 documents in reference.bio
For the example of the samples/invalid.bio, we can run
seqscore validate --labels BIO samples/invalid.bio:
Encountered 1 errors in 1 tokens, 2 sequences, and 1 documents in invalid.bio
Invalid transition 'O' -> 'I-ORG' for token 'University' on line 7
We can convert a file from one chunk encoding to another. For example,
seqscore convert --input-labels BIO --output-labels BIOES samples/reference.bio samples/reference.bioes
will read samples/reference.bio in BIO encoding and write the
BIOES-converted file to samples/reference.bioes:
This O
is O
a O
sentence O
. O
University B-ORG
of I-ORG
Pennsylvania E-ORG
is O
in O
West B-LOC
Philadelphia E-LOC
, O
Pennsylvania S-LOC
. O
We can get a list of available chunk encodings by running seqscore convert --help:
Usage: seqscore convert [OPTIONS] FILE OUTPUT_FILE
Options:
--file-encoding TEXT [default: UTF-8]
--ignore-comment-lines
--ignore-document-boundaries / --use-document-boundaries
--output-delim TEXT [default: space]
--input-labels [BIO|BIOES|BILOU|BMES|BMEOW|IO|IOB]
[required]
--output-labels [BIO|BIOES|BILOU|BMES|BMEOW|IO|IOB]
[required]
--help Show this message and exit.
We can also apply repair methods to a file, creating an output file with only valid
transitions. For example, we can run
seqscore repair --labels BIO --repair-method conlleval samples/invalid.bio samples/invalid_repair_conlleval.bio,
which will apply the conlleval repair method to the
samples/invalid.bio and write the repaired labels to
samples/invalid_repair_conlleval.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
If we want to apply the discard repair method, we can run
seqscore repair --labels BIO --repair-method discard samples/invalid.bio samples/invalid_repair_discard.bio
and the output will be written to
samples/invalid_repair_discard.bio:
This O
is O
a O
sentence O
. O
University O
of O
Pennsylvania O
is O
in O
West B-LOC
Philadelphia I-LOC
, O
Pennsylvania B-LOC
. O
Repairing the file before performing other operations is available in the count and
summarize subcommands.
The summarize subcommand can produce counts of the types of chunks in the input file.
For example, if we run seqscore summarize --labels BIO samples/reference.bio we get
the following output:
File 'samples/reference.bio' contains 1 document(s) with the following mentions:
| Entity Type | Count |
|---------------|---------|
| LOC | 2 |
| ORG | 1 |
If the quiet (-q) flag is provided, the first line giving the filename and document
count is not printed.
The count subcommand can produce the counts of chunks in the input file. Unlike
summarize, it counts chunk-type pairs, not just types. For example, if we run
seqscore count --labels BIO samples/reference.bio --output-file counts.csv,
tab-delimited counts would be written to counts.csv as follows:
1 ORG University of Pennsylvania
1 LOC West Philadelphia
1 LOC Pennsylvania
You can also call count without the --output-file argument to print counts to
standard output. However, you may encounter Unicode issues if your terminal is not
configured properly.
You can use the --output-delim argument to change the delimiter used in the counts.
The default delimiter of tab is strongly recommended, as there is no escaping or quoting
of the names in the output.
The process subcommand can remove entity types from a file or map them to other types.
Removing types can be performed by specifying one of --keep-types or --remove-types.
For example, if we wanted to keep only the ORG type, we could run:
seqscore process --labels BIO --keep-types ORG samples/reference.bio samples/keep_ORG.bio,
and the following output will be written to
samples/keep_ORG.bio:
This O
is O
a O
sentence O
. O
University B-ORG
of I-ORG
Pennsylvania I-ORG
is O
in O
West O
Philadelphia O
, O
Pennsylvania O
. O
You can also keep multiple types by specifying a comma-separated list of types:
--keep-types LOC,ORG.
Instead of specifying which types to keep, we can also specify which types to remove
using --remove-types. For example, if we wanted to remove only the ORG type, we could
run:
seqscore process --labels BIO --remove-types ORG samples/reference.bio samples/remove_ORG.bio,
and the following output will be written to
samples/remove_ORG.bio:
This O
is O
a O
sentence O
. O
University O
of O
Pennsylvania O
is O
in O
West B-LOC
Philadelphia I-LOC
, O
Pennsylvania B-LOC
. O
As with keep, you can specify multiple tags to remove, for example
--remove-types LOC,ORG.
The --type-map argument allows you to specify a JSON file that specifies a mapping
between types and other types. Suppose you want to collapse several types into a more
generic NAME type. In that case, the type map would be specified as follows:
{
"NAME": ["LOC", "ORG"]
}
The type map must be a JSON dictionary. The keys are the types to be mapped to, while the value for each key is a list of types to be mapped from. Note that the value must always be a list, even if it would only contain one element.
We can apply the above type map to a file using the following command:
seqscore process --labels BIO --type-map samples/type_map_NAME.json samples/reference.bio samples/all_NAME.bio,
resulting in this output:
This O
is O
a O
sentence O
. O
University B-NAME
of I-NAME
Pennsylvania I-NAME
is O
in O
West B-NAME
Philadelphia I-NAME
, O
Pennsylvania B-NAME
. O
When --type-map is specified at the same time as --keep-types or --remove-types,
the type mapping is applied before the keep/remove filtering is applied.
The extract-text subcommand extracts the text from a CoNLL-format file.
For example, to extract the text from samples/reference.bio and write it to
reference.txt, run the following command:
seqscore extract-text samples/reference.bio reference.txt
This would result in reference.txt having the following contents:
This is a sentence .
University of Pennsylvania is in West Philadelphia , Pennsylvania .
Each sentence is written on one line with space-delimited tokens.
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.
The --labels argument must be specified for commands where knowing the label encoding
is essential to getting correct answers. These commands are validate, repair, and
score. For all other commands, --labels BIO is assumed by default but can be
overridden.
The following instructions are for the project maintainers only.
For development, check out the dev branch (latest, but less tested than main).
- Create an environment:
uv venv --python 3.10 .venv - Install seqscore and development dependencies:
uv pip install -e ".[dev]"
- Create an environment:
conda create -yn seqscore python=3.10 - Activate the environment:
conda activate seqscore - Install seqscore:
pip install -e . - Install development dependencies:
pip install -e ".[dev]"
The release script is located at scripts/release.sh and can only be used by project
maintainers. To make a release:
- Make sure
__version__is up to date inseqscore/__init__.py. - Make sure you are on the main branch with no uncommitted changes.
- Run
scripts/release.sh. If anything goes wrong between tagging and releasing, you will have to delete the tag on GitHub and try again.
SeqScore was developed by the BLT Lab at Brandeis University under the direction of PI and lead developer Constantine Lignos. Chester Palen-Michel, Nolan Holley, and Claire Wang contributed to its development. Gordon Dou, Maya Kruse, and Andrew Rueda gave feedback on its features and assisted in README writing.