Triple

T12844897
Position Surface form Disambiguated ID Type / Status
Subject Shoal Creek E307147 entity
Predicate flowsThrough P225 FINISHED
Object Kansas E30311 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: Kansas | Statement: [Shoal Creek, flowsThrough, Kansas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kansas
Context triple: [Shoal Creek, flowsThrough, Kansas]
  • A. Kansas chosen
    Kansas is a largely rural, landlocked U.S. state known for its extensive plains, agricultural production, and central location within the country.
  • B. Kansas, Georgia
    Kansas, Georgia is a small unincorporated rural community located in Carroll County in the western part of the state.
  • C. Kansas, Alabama
    Kansas, Alabama is a small unincorporated rural community located in Walker County in the U.S. state of Alabama.
  • D. Nebraska
    Nebraska is a landlocked U.S. state on the Great Plains known for its agriculture, prairies, and role as a historic crossroads for westward expansion.
  • E. Nebraska
    Nebraska is a 2013 black-and-white American road comedy-drama film directed by Alexander Payne that follows an aging man's quixotic journey to claim a supposed sweepstakes prize.
  • 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_69d7bdf52b94819096d6f0ba4ab50a98 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96ff3a7208190b93f6292ed5efc07 completed April 10, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69b9fa40c8190bbc2c6ad22795de4 completed May 3, 2026, 12:49 a.m.
Created at: April 9, 2026, 5:36 p.m.