Triple

T9825237
Position Surface form Disambiguated ID Type / Status
Subject Hoosiers E238637 entity
Predicate filmingLocation P40 FINISHED
Object Indiana E32567 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: Indiana | Statement: [Hoosiers, filmingLocation, Indiana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Indiana
Context triple: [Hoosiers, filmingLocation, Indiana]
  • A. Indiana chosen
    Indiana is a U.S. state known for its manufacturing base, rich agricultural land, and iconic events like the Indianapolis 500.
  • B. Hoosier State
    The Hoosier State was a passenger train service that operated between Chicago, Illinois, and Indianapolis, Indiana, providing regional rail transportation in the Midwestern United States.
  • C. Indiana and Kentucky
    Indiana and Kentucky are neighboring U.S. states in the Midwest and Upper South, respectively, separated in large part by the Ohio River.
  • D. Illinois
    Illinois is a Midwestern U.S. state known for its major metropolis Chicago, diverse economy, and significant political and transportation influence.
  • E. Ohio
    Ohio is a Midwestern U.S. state known for its diverse economy, major cities like Columbus, Cleveland, and Cincinnati, and its significant role in national politics as a historic swing 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_69ca84e0dd1881909800765d1e21f735 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3181c688190afea3b27ee392a30 completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1eacbc2348190bac1cc7f41a389b9 completed April 5, 2026, 4:53 a.m.
Created at: March 30, 2026, 8:31 p.m.