Triple

T7007605
Position Surface form Disambiguated ID Type / Status
Subject Badger, Missouri E162495 entity
Predicate hasName P744 FINISHED
Object Badger, Missouri E162495 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: Badger, Missouri | Statement: [Badger, Missouri, hasName, Badger, Missouri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Badger, Missouri
Context triple: [Badger, Missouri, hasName, Badger, Missouri]
  • A. Badger, Missouri chosen
    Badger, Missouri is a small unincorporated community located in rural Vernon County in the western part of the state.
  • B. Elkhorn, Missouri
    Elkhorn, Missouri is a small unincorporated rural community located in Ray County in the U.S. state of Missouri.
  • C. Sibley, Missouri
    Sibley, Missouri is a small village in western Missouri known for its proximity to the historic Fort Osage site along the Missouri River.
  • D. Skidmore, Missouri
    Skidmore, Missouri is a small rural town in northwest Missouri known for its agricultural setting and a few high-profile criminal cases that have drawn national attention.
  • E. Bellamy, Missouri
    Bellamy, Missouri is a small unincorporated community located in rural Vernon County in the western part of the state.
  • 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_69c6885928148190ae31909fbb5e9849 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dc36e3fc8190957445132a9ffb5f completed March 27, 2026, 7:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a43c3a081909b9150d36ba107f5 completed March 28, 2026, 5:42 a.m.
Created at: March 27, 2026, 2:33 p.m.