Triple

T7853128
Position Surface form Disambiguated ID Type / Status
Subject Anita Louise E182104 entity
Predicate placeOfBirth P1 FINISHED
Object New York E40 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: New York | Statement: [Anita Louise, placeOfBirth, New York]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: New York
Context triple: [Anita Louise, placeOfBirth, New York]
  • A. New York
    New York is a populous and economically significant U.S. state known for New York City, a global center of finance, culture, and media.
  • 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. Washington, New York
    Washington, New York is a rural town in Dutchess County known for its historic hamlet of Millbrook, scenic landscapes, and equestrian and agricultural heritage.
  • D. NYC
    NYC is a historic American railroad company that operated major passenger and freight services across the northeastern and midwestern United States.
  • E. 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.
  • 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_69ca82869ee08190b8f9040dbc2c0467 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb18ed56d481909266d862e0ae152d completed March 31, 2026, 12:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5a0a34fc81908e7852ed0dbc377c completed March 31, 2026, 5:22 a.m.
Created at: March 30, 2026, 4:51 p.m.