Triple

T3526643
Position Surface form Disambiguated ID Type / Status
Subject Welwyn Garden City E74554 entity
Predicate hasNearbyMotorway P385 FINISHED
Object A1(M) E160628 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: A1(M) | Statement: [Welwyn Garden City, hasNearbyMotorway, A1(M)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: A1(M)
Context triple: [Welwyn Garden City, hasNearbyMotorway, A1(M)]
  • A. A1(M) chosen
    A1(M) is a series of motorway-standard sections in England that upgrade parts of the historic A1 route between London and the North.
  • B. M1
    M1 is a boat line that operates as part of Geneva’s public transport network, providing passenger service across the city’s waters.
  • C. M1
    M1 is Budapest’s historic Millennium Underground line, one of the world’s oldest metro lines and a UNESCO World Heritage site.
  • D. M1
    M1 is the first and primary north–south metro line of the Warsaw Metro system in Poland.
  • E. M1
    M1 is one of the main lines of the Copenhagen Metro, providing rapid transit service through central Copenhagen and connecting key residential and commercial areas.
  • 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_69ad85d0c5488190a3d8e02ebd01a1aa completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc6bb0748190bfccfe25d2ab41b7 completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e90e67c81909944bb81d89e039b completed March 13, 2026, 3:03 a.m.
Created at: March 8, 2026, 3:19 p.m.