Triple

T21352668
Position Surface form Disambiguated ID Type / Status
Subject Maine State Route 32 E526528 entity
Predicate abbreviation P43 FINISHED
Object Route 32 — 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: Route 32 | Statement: [Maine State Route 32, abbreviation, Route 32]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Route 32
Context triple: [Maine State Route 32, abbreviation, Route 32]
  • A. Route 32
    Route 32 is a state highway in New York that runs through several communities in the Hudson Valley and central parts of the state.
  • B. Route 32 chosen
    Route 32 is a state highway in Connecticut that runs generally north–south, serving as a key regional route through several towns and cities.
  • C. Route 32
    Route 32 is a major highway in Costa Rica that connects the capital city of San José with the Caribbean port city of Limón, serving as a key transportation corridor across the country.
  • D. Route 33
    Route 33 is a state highway in Connecticut that runs through Fairfield County, connecting several suburban communities and serving as a local commuter route.
  • E. Route 30
    Route 30 is a state highway in Connecticut that serves as a regional connector through several towns in the north-central part of the state.
  • 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_69e0b51cd5cc81909ac1187971e8a8ad completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8ad34a1d48190b14fa099968faf7c completed April 22, 2026, 11:12 a.m.
Created at: April 16, 2026, 5:05 p.m.