Triple

T10076215
Position Surface form Disambiguated ID Type / Status
Subject Stadt Fürth E213765 entity
Predicate twinCity P1072 FINISHED
Object Paisley E25349 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: Paisley | Statement: [Stadt Fürth, twinCity, Paisley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paisley
Context triple: [Stadt Fürth, twinCity, Paisley]
  • A. Paisley chosen
    Paisley is a large town in the west of Scotland known for its historic textile industry and as the origin of the famous paisley pattern.
  • B. Paisley
    Paisley is a small rural village in Bruce County, Ontario, Canada, known for its location at the confluence of the Saugeen and Teeswater Rivers and its historic downtown.
  • C. Motherwell
    Motherwell is a former industrial town in North Lanarkshire, Scotland, historically known as a major center of the steel industry.
  • D. Motherwell
    Motherwell is a large township in the Eastern Cape province of South Africa, situated within the Nelson Mandela Bay Metropolitan Municipality and known for its dense residential communities and socio-economic challenges.
  • E. Uddingston
    Uddingston is a suburban town in Scotland, situated near Glasgow and known for its residential character and local amenities.
  • 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_69ca839add308190b57d53b4ec21f2d0 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd0190d808190847ea0fa401ef06c completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cbc0388c8190bc10d462068c9e38 completed April 5, 2026, 8:53 p.m.
Created at: March 30, 2026, 8:59 p.m.