Triple

T21342369
Position Surface form Disambiguated ID Type / Status
Subject Massachusetts Route 135 E526228 entity
Predicate hasJunctionWith P1018 FINISHED
Object Route 30 — 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 30 | Statement: [Massachusetts Route 135, hasJunctionWith, Route 30]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Route 30
Context triple: [Massachusetts Route 135, hasJunctionWith, Route 30]
  • A. Route 30 chosen
    Route 30 is a major east–west highway in Massachusetts that serves as a key commercial and commuter corridor through communities such as Framingham.
  • B. 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.
  • 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 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.
  • E. Route 32
    Route 32 is a state highway in Connecticut that runs generally north–south, serving as a key regional route through several towns and cities.
  • 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_69e0b51c33048190ab27cede74ef798c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8a850617081909bf5c1ecc84d55b1 completed April 22, 2026, 10:52 a.m.
Created at: April 16, 2026, 4:44 p.m.