Triple

T13202487
Position Surface form Disambiguated ID Type / Status
Subject The Drunkenness of Noah (Michelangelo fresco) E314274 entity
Predicate showsFigure P66682 FINISHED
Object Ham E381221 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: Ham | Statement: [The Drunkenness of Noah (Michelangelo fresco), showsFigure, Ham]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ham
Context triple: [The Drunkenness of Noah (Michelangelo fresco), showsFigure, Ham]
  • A. Ham
    Ham is a municipality in the Belgian province of Limburg, known for its rural character and location in the Flemish Region.
  • B. Ham
    Ham is a suburban riverside district in southwest London, England, known for its historic houses, green spaces, and proximity to the River Thames.
  • C. Ham
    Ham is a small town in the Somme department of northern France, known historically for its medieval fortress and strategic location.
  • D. Ham chosen
    Ham is a biblical figure known as one of Noah’s sons and a progenitor of several ancient peoples mentioned in the Hebrew Bible.
  • E. HAM
    HAM is the IATA airport code for Hamburg Airport, the international airport serving the city of Hamburg, Germany.
  • 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_69d806aee7308190b70a237ba2a6e3e1 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98f71c5388190a6e122e14384efd7 completed April 11, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff1a3d68819089ad35f8f9ff5c5a completed May 3, 2026, 7:54 a.m.
Created at: April 9, 2026, 9:16 p.m.