Triple

T15492932
Position Surface form Disambiguated ID Type / Status
Subject Harry Woods E378741 entity
Predicate filmographyIncludes P15620 FINISHED
Object Dodge City E26181 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: Dodge City | Statement: [Harry Woods, filmographyIncludes, Dodge City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dodge City
Context triple: [Harry Woods, filmographyIncludes, Dodge City]
  • A. Dodge City, Kansas chosen
    Dodge City, Kansas is a historic frontier town in southwestern Kansas known for its Old West heritage, cattle trade history, and role as a major stop along the Santa Fe Trail.
  • B. Wichita
    Wichita is a small unincorporated community located in Guthrie County, Iowa.
  • C. Wichita
    Wichita is a 1955 American Western film starring Joel McCrea as lawman Wyatt Earp in the turbulent Kansas cattle town.
  • D. Wichita
    Wichita is a savvy, resourceful con artist and one of the central survivors in the post-apocalyptic comedy film "Zombieland."
  • E. El Reno
    El Reno is a small city in central Oklahoma known for its historic Route 66 ties, annual fried onion burger festival, and role as a regional agricultural and transportation hub.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fad723481908d2aa33e8f065f2f completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3660fc6c81908caf1729260a8338 completed May 9, 2026, 1:28 p.m.
Created at: April 10, 2026, 3:49 a.m.