Triple

T12714756
Position Surface form Disambiguated ID Type / Status
Subject Connecticut Route 10 E303807 entity
Predicate passesThrough P225 FINISHED
Object Farmington E60596 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: Farmington | Statement: [Connecticut Route 10, passesThrough, Farmington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Farmington
Context triple: [Connecticut Route 10, passesThrough, Farmington]
  • A. Farmington
    Farmington is a small city in Davis County, Utah, known as a suburban community between Salt Lake City and Ogden and as the home of the Lagoon amusement park.
  • B. Farmington
    Farmington is a city in northwestern New Mexico known as a regional hub for energy production and outdoor recreation near the Four Corners area.
  • C. Farmington
    Farmington is a small unincorporated community in San Joaquin County, California, situated in the state’s Central Valley.
  • D. Marford
    Marford is a village in Wrexham County Borough, Wales, known for its distinctive Gothic-style architecture and historic character.
  • E. Farmington, Connecticut chosen
    Farmington, Connecticut is a suburban town in central Connecticut known for its affluent residential character, historic New England charm, and role as a base for major corporate and educational institutions.
  • 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_69d7bdf084148190ab9d513dc0735af4 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9620a7554819083784897ff690652 completed April 10, 2026, 8:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671bad5108190915d14c3ec3d2e27 completed May 2, 2026, 9:50 p.m.
Created at: April 9, 2026, 5:23 p.m.