Triple

T10546355
Position Surface form Disambiguated ID Type / Status
Subject Lisa Yuskavage E248826 entity
Predicate placeOfBirth P1 FINISHED
Object Pennsylvania E13698 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Pennsylvania | Statement: [Lisa Yuskavage, placeOfBirth, Pennsylvania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pennsylvania
Context triple: [Lisa Yuskavage, placeOfBirth, Pennsylvania]
  • A. Pennsylvania chosen
    Pennsylvania is a historically significant U.S. state in the Mid-Atlantic and Northeastern regions, known for cities like Philadelphia and Pittsburgh and its central role in the nation’s founding.
  • B. Pensilvania
    Pensilvania is a municipality and town located in the Caldas Department of Colombia, known for its coffee-growing economy and mountainous Andean landscape.
  • C. Pennsylvania and New Jersey
    Pennsylvania and New Jersey are neighboring U.S. states in the Mid-Atlantic region, separated for much of their length by the Delaware River.
  • D. Penn
    Penn is the stage and given name of Penn Jillette, the outspoken magician, comedian, and half of the famed duo Penn & Teller.
  • E. Penn
    Penn is a 2006 Tamil-language romantic comedy film directed by A. Venkatesh and produced by AVM Productions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d381c733c08190ab1dd6239f5f34ae completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5191345ac81909bc404ba9574ce4c completed April 7, 2026, 2:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69d9344a53fc81909765061d07d0cd20 completed April 10, 2026, 5:32 p.m.
Created at: April 6, 2026, 12:33 p.m.