Word-level explanations of text reuse in Latin literature: align a reusing passage to its source and name the operation behind every link.
See the code
Word-level explanations of text reuse in Latin literature.
When a later author quotes or alludes to an earlier one, the interesting question is how the source was reworked. Retexo answers it word by word: it aligns every word of the reusing passage to the source word it takes up, or to none, and names the operation behind each link, such as a copy, a change of inflection, or a substitution. The result is an edit script: a set of labeled links between two passages that a philologist can read and contest.
Retexo learns these scripts from very little annotation. Synthetic pairs, built by applying known operations to Latin text, teach a pointer network the task before a single pair is annotated, and active learning chooses the few pairs an annotator corrects.
pip install retexo
Read the predictions, with the Hugging Face datasets library:
from datasets import load_dataset
scripts = load_dataset("julian-schelb/latin-classical-intertextuality-edit-scripts", split="fold_4")
pair = scripts[0]
for link in pair["links"]:
print(pair["reuse"]["tokens"][link["reuse"]], "<-", pair["source"]["tokens"][link["source"]], link["label"])
Convert the raw predictions of a run into the same format:
retexo export runs/f0/predictions.jsonl runs/f1/predictions.jsonl runs/f2/predictions.jsonl \
runs/f3/predictions.jsonl runs/f4/predictions.jsonl --out export/ --format parquet
| Label | Meaning |
|---|---|
COPY | the same form, spelling variants folded |
INFLECT | the same lemma in another form |
SUBST | another lemma in the same slot, optionally with a named relation such as a synonym |
SPLIT, MERGE | two reuse words for one source word, or one for two |
INS, FRAME, DEL | an unlinked reuse word, a word of a citing formula, an unclaimed source word |
See the documentation for the conventions.
src/retexo/ the package: model, generator, active learning, baselines, scorer
src/retexo_gui/ Gradio demo and annotation app (gui extra)
tests/ pytest suite
examples/ notebooks on the operations, the generator, the passage class and the decoder
docs/ documentation (MkDocs)
webapp/ the review app (React, Vite), published under /demo/
The experiments behind the paper live in a separate repository that installs retexo as a dependency.
pip install -e ".[dev,lexical]"
pytest
mkdocs serve
See docs/development.md.
Julian Schelb (University of Konstanz), Michael Wittweiler (University of Zurich), Marie Revellio (University of Konstanz).
MIT
Word-level explanations of text reuse in Latin literature: align a reusing passage to its source and name the operation behind every link.
See the code
Word-level explanations of text reuse in Latin literature.
When a later author quotes or alludes to an earlier one, the interesting question is how the source was reworked. Retexo answers it word by word: it aligns every word of the reusing passage to the source word it takes up, or to none, and names the operation behind each link, such as a copy, a change of inflection, or a substitution. The result is an edit script: a set of labeled links between two passages that a philologist can read and contest.
Retexo learns these scripts from very little annotation. Synthetic pairs, built by applying known operations to Latin text, teach a pointer network the task before a single pair is annotated, and active learning chooses the few pairs an annotator corrects.
pip install retexo
Read the predictions, with the Hugging Face datasets library:
from datasets import load_dataset
scripts = load_dataset("julian-schelb/latin-classical-intertextuality-edit-scripts", split="fold_4")
pair = scripts[0]
for link in pair["links"]:
print(pair["reuse"]["tokens"][link["reuse"]], "<-", pair["source"]["tokens"][link["source"]], link["label"])
Convert the raw predictions of a run into the same format:
retexo export runs/f0/predictions.jsonl runs/f1/predictions.jsonl runs/f2/predictions.jsonl \
runs/f3/predictions.jsonl runs/f4/predictions.jsonl --out export/ --format parquet
| Label | Meaning |
|---|---|
COPY | the same form, spelling variants folded |
INFLECT | the same lemma in another form |
SUBST | another lemma in the same slot, optionally with a named relation such as a synonym |
SPLIT, MERGE | two reuse words for one source word, or one for two |
INS, FRAME, DEL | an unlinked reuse word, a word of a citing formula, an unclaimed source word |
See the documentation for the conventions.
src/retexo/ the package: model, generator, active learning, baselines, scorer
src/retexo_gui/ Gradio demo and annotation app (gui extra)
tests/ pytest suite
examples/ notebooks on the operations, the generator, the passage class and the decoder
docs/ documentation (MkDocs)
webapp/ the review app (React, Vite), published under /demo/
The experiments behind the paper live in a separate repository that installs retexo as a dependency.
pip install -e ".[dev,lexical]"
pytest
mkdocs serve
See docs/development.md.
Julian Schelb (University of Konstanz), Michael Wittweiler (University of Zurich), Marie Revellio (University of Konstanz).
MIT