Triple

T1868143
Position Surface form Disambiguated ID Type / Status
Subject Charles Warren Fairbanks E34969 entity
Predicate stateRepresented P192 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: [Charles Warren Fairbanks, stateRepresented, Indiana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Indiana
Context triple: [Charles Warren Fairbanks, stateRepresented, 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. 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.
  • C. Illinois
    Illinois is a Midwestern U.S. state known for its major metropolis Chicago, diverse economy, and significant political and transportation influence.
  • D. 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.
  • E. Michigan
    Michigan is a U.S. state in the Great Lakes region known for its extensive freshwater coastline, automotive industry centered in Detroit, and diverse natural landscapes.
  • 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_69a88600b2f88190bc09303e68ab517e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abb0b6ac108190921c197abc5ab5b5 completed March 7, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfb7eeda88190bdedb28497fbd81e completed March 8, 2026, 10:43 p.m.
Created at: March 4, 2026, 7:34 p.m.