Triple

T14625679
Position Surface form Disambiguated ID Type / Status
Subject Woods County E343337 entity
Predicate hasSettlement P1068 FINISHED
Object Waynoka E208844 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: Waynoka | Statement: [Woods County, hasSettlement, Waynoka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waynoka
Context triple: [Woods County, hasSettlement, Waynoka]
  • A. Waynoka chosen
    Waynoka is a small city in northwestern Oklahoma known historically as a railroad hub and as a gateway to the nearby Little Sahara State Park sand dunes.
  • B. Owaneco
    Owaneco was a prominent Mohegan sachem (chief) known for his leadership and land dealings in colonial New England during the late 17th and early 18th centuries.
  • C. Looma
    Looma is an alternative name for Loma, which may refer to various places, peoples, or entities sharing that designation.
  • D. Tallassee
    Tallassee is a small city in central Alabama known for its location along the Tallapoosa River and its historic textile mill heritage.
  • E. Walatowa
    Walatowa is the traditional Towa name for Jemez Pueblo, a Native American community in north-central New Mexico known for its rich cultural and linguistic heritage.
  • 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_69d822dffc3c8190aa173b90761bffda completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb46a4a9081908472b0a542028a7f completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdd5d0514081908c2bdc4fb77b1a7a completed May 8, 2026, 12:23 p.m.
Created at: April 10, 2026, 1:26 a.m.