Triple

T15335468
Position Surface form Disambiguated ID Type / Status
Subject Vermont Route 103 E366652 entity
Predicate passesThrough P225 FINISHED
Object Rutland County E626505 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: Rutland County | Statement: [Vermont Route 103, passesThrough, Rutland County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rutland County
Context triple: [Vermont Route 103, passesThrough, Rutland County]
  • A. Rutland County chosen
    Rutland County is a county in central Vermont known for its mountainous terrain, outdoor recreation, and proximity to major ski areas.
  • B. Colchester County
    Colchester County is a regional municipality in north-central Nova Scotia, Canada, known for its mix of rural communities, agricultural lands, and the town of Truro as its commercial hub.
  • C. Rowan County
    Rowan County is a county in North Carolina that lies within the greater Charlotte metropolitan region.
  • D. Bradford County
    Bradford County is a largely rural county in northern Pennsylvania known for its agricultural landscape, small towns, and location along the New York state border.
  • E. Rockingham County
    Rockingham County is a North Carolina county that forms part of the Piedmont Triad region, known for its mix of rural communities, small towns, and manufacturing history.
  • 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_69d85a1355608190a6673ddb67231d54 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e03c5f081908e4d14dbdbc7f7a6 completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff01f11b88819089342e8b088bc95e completed May 9, 2026, 9:44 a.m.
Created at: April 10, 2026, 3:17 a.m.