Triple

T5966321
Position Surface form Disambiguated ID Type / Status
Subject Black Hills E132760 entity
Predicate hasCity P316 FINISHED
Object Custer E538395 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: Custer | Statement: [Black Hills, hasCity, Custer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Custer
Context triple: [Black Hills, hasCity, Custer]
  • A. Custer chosen
    Custer is a surname most famously associated with George Armstrong Custer, the U.S. Army officer and cavalry commander who died at the Battle of the Little Bighorn.
  • B. Red Cloud
    Red Cloud was a prominent Oglala Lakota (Sioux) war leader and statesman best known for successfully leading resistance against U.S. military expansion during Red Cloud’s War in the late 1860s.
  • C. Crazy Horse
    Crazy Horse was a renowned Oglala Lakota war leader known for his role in resisting U.S. expansion, including his leadership at the Battle of the Little Bighorn.
  • D. Crazy Horse
    Crazy Horse is an American rock band best known as Neil Young’s longtime, hard-edged backing group on many of his most acclaimed albums and tours.
  • E. Crazy Horse
    Crazy Horse is a famous Parisian cabaret known for its avant-garde, artistically choreographed nude performances and distinctive use of lighting and staging.
  • 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_69c0086c2364819091e9fe2f58fa2517 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c03a3e06848190b1d1a191db257a07 completed March 22, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e3f917c881909c4f780937c5fa7b completed March 23, 2026, 6:55 a.m.
Created at: March 22, 2026, 4:03 p.m.