datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
loq-triples
LoQ Triples
Supervision for training a question generator for information extraction:
given a document and an argument role, the set of questions that best extracts
that role's arguments from that document.
The questions are not hand-written. Each is the output of an optimization loop
that drafts candidate questions, extracts arguments with them, scores the
extraction against ground truth, and rewrites from that feedback -- keeping
whichever iteration scored best.
These are the… See the full description on the dataset page: https://huggingface.co/datasets/omar-sharif03/loq-triples.geo-triples-tokyo23
geo-triples-tokyo23
510,616 spatial triples, 483,922 text rows and 8,890 evaluation questions,
computed from two frozen, openly-licensed sources by an oracle with no model
and no network in the loop. Same input and same versions, same Parquet, byte
for byte.
Three things are kept apart throughout, in the data and in this card.
YuisekinGeoSPARQL observes: it reads a DE-9IM matrix off two published
geometries. LeanGeospatial certifies: it proves what a matrix entails and
what the… See the full description on the dataset page: https://huggingface.co/datasets/yuiseki/geo-triples-tokyo23.geo-triples-japan
geo-triples-japan
510,616 spatial triples, 483,922 text rows and 8,890 evaluation questions,
computed from two frozen, openly-licensed sources by an oracle with no model
and no network in the loop. Same input and same versions, same Parquet, byte
for byte.
Three things are kept apart throughout, in the data and in this card.
YuisekinGeoSPARQL observes: it reads a DE-9IM matrix off two published
geometries. LeanGeospatial certifies: it proves what a matrix entails and
what the… See the full description on the dataset page: https://huggingface.co/datasets/yuiseki/geo-triples-japan.geo-triples-jp-gov
geo-triples-jp-gov
162,810 spatial triples, 165,670 text rows and 1,807 evaluation questions
about Japan's 47 prefectures and 1,909 municipalities, computed from two
frozen government registers by an oracle with no model and no network in the
loop. Same input and same versions, same Parquet, byte for byte.
CC-BY-4.0. Attribution is required and share-alike is not, which is the
reason this dataset exists apart from
geo-triples-japan,
its ODbL sibling built from OpenStreetMap. One… See the full description on the dataset page: https://huggingface.co/datasets/yuiseki/geo-triples-jp-gov.