Triple

T15549387
Position Surface form Disambiguated ID Type / Status
Subject Steuben County, Indiana E370699 entity
Predicate hasLargestCity P235 FINISHED
Object Angola, Indiana E1163199 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: Angola, Indiana | Statement: [Steuben County, Indiana, hasLargestCity, Angola, Indiana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Angola, Indiana
Context triple: [Steuben County, Indiana, hasLargestCity, Angola, Indiana]
  • A. Angola, Indiana chosen
    Angola, Indiana is a small city in northeastern Indiana known as a regional hub for education, commerce, and access to the area’s many lakes.
  • B. Apalona, Indiana
    Apalona, Indiana is an unincorporated rural community located in Perry County in the southern part of the state.
  • C. Ceylon, Indiana
    Ceylon, Indiana is a small unincorporated rural community located in Adams County in the northeastern part of the state.
  • D. Zulu, Indiana
    Zulu, Indiana is a small unincorporated rural community located in Adams County in the northeastern part of the state.
  • E. Loogootee, Indiana
    Loogootee, Indiana is a small city in southwestern Indiana known for its tight-knit community and strong high school basketball tradition.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04a93121881909d88ca55a39252ac completed April 16, 2026, 2:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c3e67c881909a9fa1e483a364be completed May 9, 2026, 3:01 p.m.
Created at: April 10, 2026, 4:08 a.m.