Triple

T4465165
Position Surface form Disambiguated ID Type / Status
Subject Getty Square E98359 entity
Predicate partOf P40 FINISHED
Object downtown Yonkers E17729 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: downtown Yonkers | Statement: [Getty Square, partOf, downtown Yonkers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: downtown Yonkers
Context triple: [Getty Square, partOf, downtown Yonkers]
  • A. Yonkers, New York chosen
    Yonkers, New York is a major suburban city just north of New York City, known for its historic waterfront, diverse neighborhoods, and role as one of the largest cities in the state.
  • B. Yonkers Waterfront
    Yonkers Waterfront is a revitalized riverside district along the Hudson River in Yonkers, New York, known for its parks, promenades, dining, and residential developments.
  • C. Downtown Brooklyn
    Downtown Brooklyn is a major commercial and civic hub of Brooklyn, New York City, known for its government buildings, office towers, shopping centers, and growing residential developments.
  • D. Downtown
    Downtown is an American television series featuring Mariska Hargitay in a leading role.
  • E. downtown Albany
    Downtown Albany is the central business and governmental district of Albany, New York, featuring state offices, historic architecture, and a concentration of commercial and cultural institutions.
  • 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_69b3454a7c608190944f5455c8031d73 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35697937c8190b91f72d9e4f945f6 completed March 13, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69b6285164b081908f144e74ae3a1be8 completed March 15, 2026, 3:32 a.m.
Created at: March 12, 2026, 11:34 p.m.