Triple

T19962353
Position Surface form Disambiguated ID Type / Status
Subject LEED-CS E479845 entity
Predicate supportsCertificationLevel P59357 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: [LEED-CS, supportsCertificationLevel, Gold]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gold
Context triple: [LEED-CS, supportsCertificationLevel, 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 chosen
    Gold is a chemical element and precious metal highly valued for its rarity, luster, and use in jewelry, currency, and electronics.
  • C. 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.
  • 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_69d8e523c19881909f9197037200dde6 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65af51b4c81909ba156a489cbc551 completed April 20, 2026, 4:57 p.m.
Created at: April 10, 2026, 1:54 p.m.