Triple

T7742649
Position Surface form Disambiguated ID Type / Status
Subject Paul Kiparsky E175546 entity
Predicate hasAcademicAdvisor P167 FINISHED
Object Morris Halle E32214 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: Morris Halle | Statement: [Paul Kiparsky, hasAcademicAdvisor, Morris Halle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Morris Halle
Context triple: [Paul Kiparsky, hasAcademicAdvisor, Morris Halle]
  • A. Morris Halle chosen
    Morris Halle was a pioneering Latvian-American linguist and phonologist, best known for his foundational work in generative phonology and his long collaboration with Noam Chomsky at MIT.
  • B. Tan Hall
    Tan Hall is a major academic and research building associated with the College of Chemistry at the University of California, Berkeley.
  • C. Silverman Hall
    Silverman Hall is a prominent academic and administrative building that serves as a central facility of the University of Pennsylvania Law School.
  • D. Julius Ochs Adler
    Julius Ochs Adler was an American newspaper executive, publisher of The New York Times, and U.S. Army officer who rose to the rank of major general.
  • E. Joseph Bloor
    Joseph Bloor was a 19th-century Canadian entrepreneur, land developer, and brewer who played a key role in the early development of Toronto, Ontario.
  • 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_69c6995f9c60819092e386192bd63c6f completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c70387807081909546bc7c209955ef completed March 27, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8d6b95f108190a726bf4c6d77bb62 completed March 29, 2026, 7:37 a.m.
Created at: March 27, 2026, 4:07 p.m.