Triple

T2919239
Position Surface form Disambiguated ID Type / Status
Subject The Royal Tenenbaums E78678 entity
Predicate setting P1957 FINISHED
Object New York City 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 City | Statement: [The Royal Tenenbaums, setting, New York City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: New York City
Context triple: [The Royal Tenenbaums, setting, New York City]
  • A. New York City chosen
    New York City is the largest city in the United States, a global center of finance, culture, media, and technology.
  • B. 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.
  • C. 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.
  • D. Brooklyn
    Brooklyn is a populous and culturally diverse borough of New York City known for its distinct neighborhoods, arts scene, and iconic landmarks like the Brooklyn Bridge.
  • E. 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.
  • 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_69ad8b0c2ad081909ff87050ae542bb9 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad96a53f8c8190b188d549f1161e84 completed March 8, 2026, 3:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0555c43348190a99f6d11031417b3 completed March 10, 2026, 5:31 p.m.
Created at: March 8, 2026, 2:54 p.m.