Triple

T19938659
Position Surface form Disambiguated ID Type / Status
Subject M180 motorway E479243 entity
Predicate passesNear P416 FINISHED
Object Thorne NE NERFINISHED

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: Thorne | Statement: [M180 motorway, passesNear, Thorne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thorne
Context triple: [M180 motorway, passesNear, Thorne]
  • A. Thorne
    Thorne is a surname most prominently associated with Kip Thorne, the Nobel Prize–winning theoretical physicist known for his work on gravitation and black holes.
  • B. Thorne chosen
    Thorne is a small market town in South Yorkshire, England, known for its historic waterways, including canals and navigable rivers.
  • C. Thorney
    Thorney is a village in Cambridgeshire, England, historically centered around its important medieval Benedictine abbey.
  • D. Taffs Well
    Taffs Well is a village in South Wales known for its historic thermal spring and proximity to Cardiff at the southern end of the Taff Valley.
  • E. Thringstone
    Thringstone is a village in Leicestershire, England, known for its historic community, former mining connections, and proximity to the town of Coalville.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e522a17c819095165d4d24939fd8 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65a190ac08190b9dc7955c9764a71 completed April 20, 2026, 4:53 p.m.
Created at: April 10, 2026, 1:53 p.m.