Triple

T1372016
Position Surface form Disambiguated ID Type / Status
Subject London King’s Cross E30132 entity
Predicate servesDestination P2066 FINISHED
Object Inverness E50911 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: Inverness | Statement: [London King’s Cross, servesDestination, Inverness]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Inverness
Context triple: [London King’s Cross, servesDestination, Inverness]
  • A. Inverness chosen
    Inverness is a city in the Scottish Highlands that serves as a major cultural and administrative center for the region.
  • B. Greenock
    Greenock is a historic port town and former shipbuilding center on the River Clyde in western Scotland.
  • C. Aberdeen
    Aberdeen is a small rural town in the Upper Hunter region of New South Wales, Australia, known historically for its agricultural and meat-processing industries.
  • D. Aberdeen
    Aberdeen is a major port city in northeast Scotland known for its North Sea oil industry, granite architecture, and role as a regional economic and cultural hub.
  • E. Dundee
    Dundee is a coastal city in eastern Scotland known for its historic jute industry, maritime heritage, and contemporary cultural and design scene.
  • 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_69a498f912008190a376a98b207b2071 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c48e6534819090d23f3cc25093ae completed March 1, 2026, 10:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae891551c8819090f6edd70c45ff39 completed March 9, 2026, 8:47 a.m.
Created at: March 1, 2026, 7:57 p.m.