Triple

T360320
Position Surface form Disambiguated ID Type / Status
Subject Mayor of London E7835 entity
Predicate oversees P46 FINISHED
Object Transport for London E11100 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: Transport for London | Statement: [Mayor of London, oversees, Transport for London]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Transport for London
Context triple: [Mayor of London, oversees, Transport for London]
  • A. Transport for London chosen
    Transport for London is the local government body responsible for managing and overseeing the public transport network and major roads in Greater London.
  • B. London Underground
    The London Underground is a rapid transit system serving Greater London and surrounding areas, famous as one of the world's oldest and most extensive metro networks.
  • C. Greater Anglia
    Greater Anglia is a British train operating company that provides passenger rail services across East Anglia and parts of London and the East of England.
  • D. Arriva UK Trains
    Arriva UK Trains is a major British train operating company that manages several passenger rail franchises and services across the United Kingdom.
  • E. Thameslink
    Thameslink is a major British rail network providing cross-London services that connect destinations across the South East of England.
  • 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_69a2e7e880008190a6ad7e06e5d03007 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ebccb8d88190a31f7c443a0c8566 completed Feb. 28, 2026, 1:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3e578c1788190877cf6a346cf10d4 completed March 1, 2026, 7:06 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.