Triple

T19376232
Position Surface form Disambiguated ID Type / Status
Subject Castle Tucker E484673 entity
Predicate city P40 FINISHED
Object Wiscasset 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: Wiscasset | Statement: [Castle Tucker, city, Wiscasset]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wiscasset
Context triple: [Castle Tucker, city, Wiscasset]
  • A. Wiscasset, Maine chosen
    Wiscasset, Maine is a historic coastal town on the Sheepscot River known for its well-preserved 18th- and 19th-century architecture and reputation as one of New England’s most picturesque villages.
  • B. Leominster
    Leominster is a historic market town in Herefordshire, England, known for its medieval architecture and agricultural heritage.
  • C. Hallowell
    Hallowell is a surname of English origin borne by various notable individuals, including figures in American education, reform, and public life.
  • D. Willimansett
    Willimansett is a residential neighborhood and village within the city of Chicopee in western Massachusetts, located along the Connecticut River.
  • E. Fitchburg
    Fitchburg is a small city in north-central Massachusetts known for its industrial history, hilly terrain, and role as a regional rail hub.
  • 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_69d8e8d460d88190abf0591c5c9d2b0c completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e61a5c05c08190b91cb32fdb79813b completed April 20, 2026, 12:21 p.m.
Created at: April 10, 2026, 1:35 p.m.