Triple

T676263
Position Surface form Disambiguated ID Type / Status
Subject Tyne and Wear Metro E13083 entity
Predicate owner P347 FINISHED
Object Nexus E83363 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: Nexus | Statement: [Tyne and Wear Metro, owner, Nexus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nexus
Context triple: [Tyne and Wear Metro, owner, Nexus]
  • A. Nexus
    Nexus is the original World Wide Web browser and editor created by Tim Berners-Lee, later renamed from its initial title "WorldWideWeb."
  • B. Nexus chosen
    Nexus is the public transport executive and passenger transport authority responsible for overseeing and managing services such as the Tyne and Wear Metro in North East England.
  • C. Telos
    Telos is an icy, subterranean planet in the Doctor Who universe best known as a major stronghold and tomb world of the Cybermen.
  • D. Nova
    Nova is the name given to TransPennine Express’s modern fleet of intercity trains used across its key routes in the North of England and Scotland.
  • E. Meraki
    Meraki is a cloud-managed IT company known for its wireless, switching, security, and device management solutions, acquired by and operating as a subsidiary of Cisco.
  • 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_69a4933d3bf88190972041cd8cf143b9 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a04b2ae881908a5c23453bef8572 completed March 1, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5dc9f5f7c8190a766c6b545d1abd8 completed March 2, 2026, 6:53 p.m.
Created at: March 1, 2026, 7:36 p.m.