Triple

T5996462
Position Surface form Disambiguated ID Type / Status
Subject Nate Silver E133481 entity
Predicate familyName P18 FINISHED
Object Silver E16227 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: Silver | Statement: [Nate Silver, familyName, Silver]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Silver
Context triple: [Nate Silver, familyName, Silver]
  • A. Silver chosen
    Silver is a lustrous, highly conductive precious metal widely used in jewelry, industry, and currency throughout history.
  • B. Gold
    Gold is a 2016 American crime adventure film in which Matthew McConaughey stars as a prospector chasing a potentially fraudulent gold discovery in the Indonesian jungle.
  • C. Gold
    Gold was the codename for one of the five Allied landing beaches used by British forces during the D-Day invasion of Normandy in World War II.
  • D. Gold
    Gold is a chemical element and precious metal highly valued for its rarity, luster, and use in jewelry, currency, and electronics.
  • E. Silver Center
    Silver Center is a historic academic building at New York University that houses classrooms, offices, and arts and science departments on the university’s Washington Square campus.
  • 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_69c00870ddbc81909880fa3864f4f38d completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04e963f3c819082dd755e328ab947 completed March 22, 2026, 8:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c10876d4d0819083ac7431c8abaedd completed March 23, 2026, 9:31 a.m.
Created at: March 22, 2026, 4:05 p.m.