Triple

T12230399
Position Surface form Disambiguated ID Type / Status
Subject Highland Lawn Cemetery E291459 entity
Predicate hasCounty P285 FINISHED
Object Vigo County E304861 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: Vigo County | Statement: [Highland Lawn Cemetery, hasCounty, Vigo County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vigo County
Context triple: [Highland Lawn Cemetery, hasCounty, Vigo County]
  • A. Vigo County, Indiana chosen
    Vigo County, Indiana is a county in western Indiana whose seat and largest city is Terre Haute, a regional hub for education, healthcare, and industry.
  • B. Vanderburgh County, Indiana
    Vanderburgh County, Indiana is a county in the southwestern part of the state that includes the city of Evansville, a major regional economic and cultural center.
  • C. Ogle County
    Ogle County is a predominantly rural county in northern Illinois known for its agricultural landscape and small communities.
  • D. Hendricks County
    Hendricks County is a county in central Indiana, United States, located just west of Indianapolis and known for its rapidly growing suburban communities.
  • E. Tippecanoe County
    Tippecanoe County is a county in northwestern Indiana known for being home to the cities of Lafayette and West Lafayette, including Purdue University.
  • 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_69d6ab668acc8190963ba424049d6aee completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91ca45bd48190b8b7f6b29b6bb25b completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce593bbc8190827ca217f43140b9 completed May 3, 2026, 10:38 p.m.
Created at: April 8, 2026, 9:51 p.m.