Triple

T1066531
Position Surface form Disambiguated ID Type / Status
Subject Georgia State Route 1 E23222 entity
Predicate passesThrough P225 FINISHED
Object LaGrange E30624 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: LaGrange | Statement: [Georgia State Route 1, passesThrough, LaGrange]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LaGrange
Context triple: [Georgia State Route 1, passesThrough, LaGrange]
  • A. LaGrange
    LaGrange is a town in Dutchess County, New York, known as a suburban community in the Hudson Valley region.
  • B. LaGrange chosen
    LaGrange is a small city in western Georgia known for its historic downtown, proximity to West Point Lake, and role as an economic and cultural center for the surrounding region.
  • C. Aiken
    Aiken is a variant spelling of the surname Aitken, which is of Scottish origin.
  • D. Greenville
    Greenville is a small city in south-central Alabama known for its historic downtown and role as the county seat of Butler County.
  • E. Greenville
    Greenville is a residential neighborhood in the southern part of Jersey City, New Jersey, known for its diverse community and urban character.
  • 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_69a493ee1f908190992b5f0d1b04459b completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b910c6d481909c56f961a0e8720c completed March 1, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac42a336388190a6d18fda8a7a151d completed March 7, 2026, 3:22 p.m.
Created at: March 1, 2026, 7:42 p.m.