Triple

T1235591
Position Surface form Disambiguated ID Type / Status
Subject Sex and the City (film) E26539 entity
Predicate filmingLocation P40 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: [Sex and the City (film), filmingLocation, New York City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: New York City
Context triple: [Sex and the City (film), filmingLocation, 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_69a4948571c88190a9191e451e6035fd completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4bf169868819090cfab7e34c40c67 completed March 1, 2026, 10:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69adfb7447408190a63a1e21b087dbf8 completed March 8, 2026, 10:43 p.m.
Created at: March 1, 2026, 7:47 p.m.