Triple

T3621090
Position Surface form Disambiguated ID Type / Status
Subject Toledo Window Box E76727 entity
Predicate producer P490 FINISHED
Object Monte Kay E447960 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: Monte Kay | Statement: [Toledo Window Box, producer, Monte Kay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monte Kay
Context triple: [Toledo Window Box, producer, Monte Kay]
  • A. Monte Kay chosen
    Monte Kay was an American jazz producer and talent manager known for his influential work in the mid-20th-century music and entertainment industry.
  • B. Monte Blue
    Monte Blue was an American film actor prominent during the silent era and early sound period, known for his leading and character roles in numerous Hollywood productions.
  • C. Mount Curwood
    Mount Curwood is a prominent peak in Michigan’s remote Huron Mountains, known as one of the state’s highest natural elevations.
  • D. Moses Mountain
    Moses Mountain is a prominent man-made hill and scenic overlook within Staten Island’s Greenbelt park system, offering hiking trails and views of the surrounding landscape.
  • E. Mount Wister
    Mount Wister is a prominent mountain peak in Wyoming’s Teton Range, known for its rugged terrain and challenging climbing routes.
  • 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_69ad85dae2fc81908d1ceadbc6af0089 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc2b9aa608190a680b250ecf63156 completed March 8, 2026, 6:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69bda3f5a8a88190a494a9338c01962a completed March 20, 2026, 7:45 p.m.
Created at: March 8, 2026, 3:23 p.m.