Triple

T21377546
Position Surface form Disambiguated ID Type / Status
Subject Interstate 465 E527250 entity
Predicate passesNear P416 FINISHED
Object Lawrence, Indiana NE NERFINISHED

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: Lawrence, Indiana | Statement: [Interstate 465, passesNear, Lawrence, Indiana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lawrence, Indiana
Context triple: [Interstate 465, passesNear, Lawrence, Indiana]
  • A. Lawrence, Indiana chosen
    Lawrence, Indiana is a suburban city in northeastern Marion County that forms part of the Indianapolis metropolitan area and includes portions of the former Fort Benjamin Harrison military base.
  • B. Lawrenceburg, Indiana
    Lawrenceburg, Indiana is a small city in southeastern Indiana along the Ohio River, known historically for its river trade and distilling industry.
  • C. Lyons, Indiana
    Lyons, Indiana is a small town located in southwestern Indiana that is part of the Bloomington metropolitan area.
  • D. Laurel, Indiana
    Laurel, Indiana is a small rural town in Franklin County known for its quiet community and agricultural surroundings.
  • E. Lancaster, Indiana
    Lancaster, Indiana is a small unincorporated rural community located in Huntington County in the U.S. state of Indiana.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51f363c8190944000ab5523b02b completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b0c8768c8190ad7cddf5cd1d06f7 completed April 22, 2026, 11:28 a.m.
Created at: April 16, 2026, 5:11 p.m.