Triple

T6483945
Position Surface form Disambiguated ID Type / Status
Subject Falkland E146461 entity
Predicate hasPostTown P2711 FINISHED
Object Cupar E21353 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: Cupar | Statement: [Falkland, hasPostTown, Cupar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cupar
Context triple: [Falkland, hasPostTown, Cupar]
  • A. Cupar chosen
    Cupar is a historic market town in eastern Scotland that once served as the county town of Fife.
  • B. Dunfermline
    Dunfermline is a historic Scottish town and former royal capital known for its medieval abbey and rich cultural heritage.
  • C. Arbirlot
    Arbirlot is a small rural village in the Angus council area of eastern Scotland, known for its historic parish church and scenic countryside setting near the North Sea coast.
  • D. Tyndrum
    Tyndrum is a small village in the Scottish Highlands that serves as a key road and rail junction for travelers heading to western and northern Scotland.
  • E. Balerno
    Balerno is a suburban village on the outskirts of Edinburgh, Scotland, known for its scenic setting near the Pentland Hills and its residential character.
  • 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_69c0090158c08190af0df9a2348d2d52 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a6de31c81909dd99d105f5bb4c2 completed March 22, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9e05085588190ba940f2a5280a57e completed March 30, 2026, 2:30 a.m.
Created at: March 22, 2026, 4:52 p.m.