Triple

T17264820
Position Surface form Disambiguated ID Type / Status
Subject New York City E419097 entity
Predicate alsoKnownAs P39 FINISHED
Object NYC NE NERFINISHED

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: NYC | Statement: [New York City, alsoKnownAs, NYC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: NYC
Context triple: [New York City, alsoKnownAs, NYC]
  • A. NYC
    NYC is a historic American railroad company that operated major passenger and freight services across the northeastern and midwestern United States.
  • B. New York City chosen
    New York City is the largest city in the United States, a global center of finance, culture, media, and technology.
  • C. Manhattan
    The Manhattan is a classic whiskey-based cocktail, traditionally made with rye or bourbon, sweet vermouth, and bitters, and typically served stirred and garnished with a cherry.
  • D. Manhattan
    Manhattan is a village in Will County, Illinois, known as a growing suburban community southwest of Chicago.
  • E. Manhattan
    Manhattan is the densely populated, iconic core borough of New York City, known for its skyscrapers, cultural institutions, and role as a global financial and media center.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d886d9ab108190b70edd8d17aa1204 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42f4432fc81908fd90865822af1fa completed April 19, 2026, 1:26 a.m.
Created at: April 10, 2026, 5:40 a.m.