Comments (4)
Thanks for reporting it! I will look into it, but in the meantime, if you are not using coreference resolution, the best solution is probably to remove xrenner from the requirements entirely.
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Thank you! Leaving out xrenner did work for now. However, I would like to have the option of using coref in the future, though it's not critical right now. Is there a chance that neuralcoref might be replaced with something like https://github.com/shon-otmazgin/fastcoref, or that it could be included as an option? Fastcoref seems to be pretty standard these days, and seems to be actively maintained.
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That looks really good at first glance, thanks for the link. I'll definitely look at adding support for it in ELEVANT.
from elevant.
I removed support for xrenner and added support for fastcoref. You can test it e.g. in combination with ReFinED on our benchmark Wiki-Fair which contains coreference ground truth mentions:
python3 link_benchmark_entities.py refined.fastcoref -l refined -coref fastcoref -b wiki-fair
Note that you cannot use a coreference linker in isolation (without specifying an entity linker), since ELEVANT evaluates the linked entities, not the coreference clusters themselves.
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Related Issues (14)
- Error while running evaluate_linking_results.py on new results file HOT 2
- Experiment working, but some parsing errors in the document display in GUI HOT 2
- Accidental experiment title cannot be expunged HOT 3
- GENRE using deprecated numpy attribute HOT 5
- Spacy model version issues? HOT 2
- Marking coref mentions in benchmark dataset HOT 4
- Article results not being displayed HOT 2
- Candidate set HOT 1
- Any plan of adding popular EL benchmarks HOT 3
- Error installing neuralcoref during docker build: Variables cannot be declared with 'cpdef'. Use 'cdef' instead. HOT 3
- make download_all: alias_to_qids.db: truncated gzip input HOT 2
- Benchmark conversion from NIF format producing incorrect results HOT 2
- Experiment with REL failed on new benchmark dataset HOT 6
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