Triple

T1564432
Position Surface form Disambiguated ID Type / Status
Subject Hal Holbrook E33399 entity
Predicate notableWork P4 FINISHED
Object Pueblo E54832 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: Pueblo | Statement: [Hal Holbrook, notableWork, Pueblo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pueblo
Context triple: [Hal Holbrook, notableWork, Pueblo]
  • A. San Luis
    San Luis is a residential and commercial district located in the eastern part of Lima, Peru.
  • B. San Luis
    San Luis is a municipality and town in western Cuba known for its agricultural activities within Pinar del Río Province.
  • C. Durango
    Durango is a state in north-central Mexico known for its rugged mountainous terrain, significant mining history, and role as a setting for classic Western films.
  • D. Wasco
    Wasco is a small agricultural city in California’s San Joaquin Valley, known historically for its rose-growing industry and farming economy.
  • E. City of Pueblo chosen
    The City of Pueblo is a home-rule municipality in southern Colorado that serves as a regional hub for industry, culture, and transportation along the Arkansas River.
  • 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_69a885f11b048190935025a035302715 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa621242188190a7e1deeada7688d8 completed March 6, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeac0be308190a12ba8e79589dead completed March 8, 2026, 9:31 p.m.
Created at: March 4, 2026, 7:27 p.m.