Triple

T14247107
Position Surface form Disambiguated ID Type / Status
Subject Darlington E353163 entity
Predicate hasName P744 FINISHED
Object Darlington unclear NED1 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: Darlington | Statement: [Darlington, hasName, Darlington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Darlington
Context triple: [Darlington, hasName, Darlington]
  • A. Darlington
    Darlington is an inner-city suburb of Sydney, New South Wales, known for its proximity to the University of Sydney and its mix of historic terraces and student housing.
  • B. Darlington
    Darlington is a surname of English origin borne by various notable individuals across fields such as engineering, science, and public life.
  • C. Darlington
    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 residential neighborhood in the city of Pawtucket, known as one of the oldest and most densely populated areas in Rhode Island.
  • E. Darlington
    Darlington is a civil parish in New South Wales, Australia, that includes the locality of Darlington Point.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de629464f88190817b190731bab156 completed April 14, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd282571ec819080d187ecec3ed925 completed May 8, 2026, 12:02 a.m.
Created at: April 10, 2026, 1:08 a.m.