Triple

T22361237
Position Surface form Disambiguated ID Type / Status
Subject Darlington, South Carolina E552782 entity
Predicate namedFor P63 FINISHED
Object Darlington, England 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: Darlington, England | Statement: [Darlington, South Carolina, namedFor, Darlington, England]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Darlington, England
Context triple: [Darlington, South Carolina, namedFor, Darlington, England]
  • A. Durham, England
    Durham, England is a historic cathedral city in northeast England known for its Norman architecture, including Durham Cathedral and Castle, and as a prominent university center.
  • B. Northfield, England
    Northfield, England is a locality in England that served as the namesake for the town of Northfield in Massachusetts, USA.
  • C. Darlington chosen
    Darlington is a market town and borough in County Durham, England, historically known for its pioneering role in railway development.
  • D. Darlington
    Darlington is a surname of English origin borne by various notable individuals across fields such as engineering, science, and public life.
  • E. Darlington
    Darlington is a rural locality in Queensland, Australia, known for its scenic landscapes and proximity to the mountainous Scenic Rim region.
  • 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_69e11e4affcc8190ba7c27d29062558d completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f157d44a908190b16e4cfdf4591b10 completed April 29, 2026, 12:59 a.m.
Created at: April 16, 2026, 8:44 p.m.