Triple

T13941579
Position Surface form Disambiguated ID Type / Status
Subject Denise Gaines E335266 entity
Predicate hasLastName P18 FINISHED
Object Gaines E895566 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: Gaines | Statement: [Denise Gaines, hasLastName, Gaines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gaines
Context triple: [Denise Gaines, hasLastName, Gaines]
  • A. Gaines chosen
    Gaines is a surname of English origin borne by various notable individuals across military, political, and cultural fields.
  • B. Burkley
    Burkley is a surname most notably associated with American character actor Dennis Burkley.
  • C. Greer
    Greer is a small city in South Carolina known for its historic downtown, proximity to both Greenville and Spartanburg, and its role as a regional industrial and transportation hub.
  • D. Greer
    Greer is a surname most notably associated with Hal Greer, a Hall of Fame American basketball player.
  • E. Overton
    Overton is a small unincorporated community in southeastern Nevada known as a gateway to the nearby Lake Mead National Recreation Area and the Valley of Fire State Park.
  • 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_69d81c6081b88190b53e317c3370c8fe completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2cf6e29881908ddb8efca9a456a3 completed April 14, 2026, 12:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce8bbd8c819084703298ed6d9c87 completed May 3, 2026, 10:39 p.m.
Created at: April 9, 2026, 10:17 p.m.