Triple

T7434517
Position Surface form Disambiguated ID Type / Status
Subject Addiewell railway station E171576 entity
Predicate between P1262 FINISHED
Object Edinburgh E16616 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: Edinburgh | Statement: [Addiewell railway station, between, Edinburgh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Edinburgh
Context triple: [Addiewell railway station, between, Edinburgh]
  • A. Edinburgh chosen
    Edinburgh is the historic and cultural heart of Scotland, renowned for its medieval Old Town, elegant Georgian New Town, and world-famous arts festivals.
  • B. Glasgow
    Glasgow is Scotland’s largest city, historically a major industrial and shipbuilding center, known for its rich cultural scene, distinctive architecture, and role as a key urban hub in the United Kingdom.
  • C. Dundee
    Dundee is a coastal city in eastern Scotland known for its historic jute industry, maritime heritage, and contemporary cultural and design scene.
  • D. Dundee
    Dundee is a small village in Yates County, New York, known for its rural character within the Finger Lakes region.
  • E. Glasgow and Edinburgh
    Glasgow and Edinburgh are Scotland’s two largest and most prominent cities, serving as major cultural, economic, and transport hubs in the country.
  • 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_69c68a64228c8190affaec2a8127ce7b completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f327480481909c4691fd3333e2ae completed March 27, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c81eb53060819081312e8b2805e9db completed March 28, 2026, 6:32 p.m.
Created at: March 27, 2026, 3:13 p.m.