Triple

T8894963
Position Surface form Disambiguated ID Type / Status
Subject Combines E211783 entity
Predicate notableWork P4 FINISHED
Object Canyon E220729 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: Canyon | Statement: [Combines, notableWork, Canyon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Canyon
Context triple: [Combines, notableWork, Canyon]
  • A. Canyon chosen
    Canyon is a famous 1959 combine painting by Robert Rauschenberg that merges traditional painting with found objects, including a stuffed bald eagle, exemplifying his radical blurring of art and everyday materials.
  • B. Canyon
    Canyon is a small city in the Texas Panhandle known as the home of West Texas A&M University and a gateway to Palo Duro Canyon State Park.
  • C. Canyon
    Canyon is a 1959 abstract expressionist painting by Helen Frankenthaler, known for its innovative soak-stain technique and luminous color fields.
  • D. La Cañada
    La Cañada is a town in the Mexican state of Querétaro that serves as the municipal seat of El Marqués.
  • E. Verdon
    Verdon is a surname most notably associated with American actress and dancer Gwen Verdon.
  • 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_69ca83918d3081909b326fa3750cb8c8 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc61be2c2081908f39cccdc149872d completed April 1, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfba212fd081909ae87853c81e1d30 completed April 3, 2026, 1:01 p.m.
Created at: March 30, 2026, 6:54 p.m.