Triple

T12439439
Position Surface form Disambiguated ID Type / Status
Subject Outfit E297231 entity
Predicate locationState P562 FINISHED
Object Illinois E13723 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: Illinois | Statement: [Outfit, locationState, Illinois]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Illinois
Context triple: [Outfit, locationState, Illinois]
  • A. Illinois chosen
    Illinois is a Midwestern U.S. state known for its major metropolis Chicago, diverse economy, and significant political and transportation influence.
  • B. Illinois 47
    Illinois 47 is a north–south state highway in Illinois that runs through both rural areas and growing suburban communities, serving as a key regional route.
  • C. Como, Illinois
    Como, Illinois is a small unincorporated community in Whiteside County that forms part of the Sterling Micropolitan Statistical Area.
  • D. Illinois and Indiana
    Illinois and Indiana are neighboring Midwestern U.S. states whose shared boundary is partly defined by the Ohio River.
  • E. Indiana
    Indiana is a U.S. state known for its manufacturing base, rich agricultural land, and iconic events like the Indianapolis 500.
  • 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_69d6ada166c48190b902972cd2408fa3 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d8dc0f881908a3da736d8947ce1 completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6556495208190abd2e3e5aaac57a5 completed May 2, 2026, 7:49 p.m.
Created at: April 8, 2026, 9:55 p.m.