Triple

T23411756
Position Surface form Disambiguated ID Type / Status
Subject Édgar Filiberto Ramírez Arellano E560086 entity
Predicate workedOn P3 FINISHED
Object Gold NE NERFINISHED

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: Gold | Statement: [Édgar Filiberto Ramírez Arellano, workedOn, Gold]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gold
Context triple: [Édgar Filiberto Ramírez Arellano, workedOn, Gold]
  • A. 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.
  • B. Gold
    Gold is a chemical element and precious metal highly valued for its rarity, luster, and use in jewelry, currency, and electronics.
  • C. Gold chosen
    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.
  • D. Gold
    "Gold" is a popular song performed by British singer Tony Hadley as the lead vocalist of the band Spandau Ballet, known for its anthemic style and enduring 1980s appeal.
  • E. Gold
    "Gold" is a satirical book by John Stewart that blends sharp humor with social and political commentary.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2454b3a5881909c64773dc8a5d289 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1a51183bc8190bd4860607b26b4b2 completed April 29, 2026, 6:28 a.m.
Created at: April 17, 2026, 5:38 p.m.