Triple

T9305636
Position Surface form Disambiguated ID Type / Status
Subject Lark bunting E223876 entity
Predicate rangeIncludes P52044 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: [Lark bunting, rangeIncludes, Kansas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kansas
Context triple: [Lark bunting, rangeIncludes, 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_69ca8424d0f08190831e2e93c6533aeb completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd1da7c1e08190af19169f5d806cde completed April 1, 2026, 1:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0b1e30c648190a2c6a8c4c6da390c completed April 4, 2026, 6:38 a.m.
Created at: March 30, 2026, 7:36 p.m.