Triple

T32743305
Position Surface form Disambiguated ID Type / Status
Subject Barry Primus E837283 entity
Predicate notableWork P4 FINISHED
Object New York, New York
"New York, New York" is a 1977 musical drama film directed by Martin Scorsese, starring Liza Minnelli and Robert De Niro, known for its exploration of a turbulent romance set against the backdrop of the post–World War II jazz scene.
E2030357 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, New York | Statement: [Barry Primus, notableWork, New York, New York]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: New York, New York
Triple: [Barry Primus, notableWork, New York, New York]
Generated description
"New York, New York" is a 1977 musical drama film directed by Martin Scorsese, starring Liza Minnelli and Robert De Niro, known for its exploration of a turbulent romance set against the backdrop of the post–World War II jazz scene.

Provenance (5 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_69f34936e1748190b797e406e4e9293a completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6cc1c33048190a17142b6c4d12470 completed May 3, 2026, 4:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34d249c5108190a63199f3fe259bbc completed June 19, 2026, 5:23 a.m.
NEDg Description generation batch_6a34d343c9ec8190b802a41f6711b6c4 completed June 19, 2026, 5:27 a.m.
NED2 Entity disambiguation (via description) batch_6a34d405a48c8190ab95daacc1a06ff5 completed June 19, 2026, 5:30 a.m.
Created at: May 1, 2026, 1:12 a.m.