Triple

T11318564
Position Surface form Disambiguated ID Type / Status
Subject Mark Hellinger Theatre E268028 entity
Predicate near P350 FINISHED
Object Times Square E471 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: Times Square | Statement: [Mark Hellinger Theatre, near, Times Square]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Times Square
Context triple: [Mark Hellinger Theatre, near, Times Square]
  • A. Times Square chosen
    Times Square is a major commercial and entertainment hub in Midtown Manhattan, famous for its bright billboards, Broadway theaters, and New Year’s Eve ball drop.
  • B. 4 Times Square
    4 Times Square is a prominent skyscraper in Midtown Manhattan known for its early adoption of green building technologies and its large illuminated signage in Times Square.
  • C. 11 Times Square
    11 Times Square is a prominent high-rise office tower in Manhattan’s Times Square district, known for its modern, sustainable design and prime commercial location.
  • D. One Times Square
    One Times Square is a famous skyscraper in New York City best known as the site of the annual New Year’s Eve ball drop in Times Square.
  • E. Union Square
    Union Square is a major commercial and cultural hub in downtown San Francisco, known for its upscale shopping, theaters, hotels, and vibrant urban plaza.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9de875481908acfa56015d4b46f completed April 9, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69e525d3160c8190b58c5c04a66b3e3e completed April 19, 2026, 6:58 p.m.
Created at: April 8, 2026, 9:32 p.m.