Triple

T15047224
Position Surface form Disambiguated ID Type / Status
Subject Madison Metro E379260 entity
Predicate alsoServes P6337 FINISHED
Object Fitchburg, Wisconsin E1082015 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: Fitchburg, Wisconsin | Statement: [Madison Metro, alsoServes, Fitchburg, Wisconsin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fitchburg, Wisconsin
Context triple: [Madison Metro, alsoServes, Fitchburg, Wisconsin]
  • A. Fitchburg, Wisconsin chosen
    Fitchburg, Wisconsin is a suburban city just south of Madison known for its blend of residential neighborhoods, business parks, and agricultural and recreational green spaces.
  • B. Farmington, Wisconsin
    Farmington, Wisconsin is a rural town in Washington County known for its agricultural landscape and small-community character in southeastern Wisconsin.
  • C. Utica, Wisconsin
    Utica, Wisconsin is a small rural town located in Winnebago County in the east-central region of the state.
  • D. Foxboro, Wisconsin
    Foxboro, Wisconsin is a small unincorporated community located in Douglas County in the northwestern part of the state.
  • E. Hartford, Wisconsin
    Hartford, Wisconsin is a small city in southeastern Wisconsin known for its manufacturing base, historic downtown, and proximity to the Kettle Moraine State Forest.
  • 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_69d85cd64d108190853797a95c11cc45 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69deda8e64e48190873104a02a676ff3 completed April 15, 2026, 12:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffa92b99c48190b76e1306cf32a568 completed May 9, 2026, 9:37 p.m.
Created at: April 10, 2026, 3 a.m.