Triple

T4053145
Position Surface form Disambiguated ID Type / Status
Subject historic county of Middlesex E84631 entity
Predicate containedSettlement P16159 FINISHED
Object Hounslow E129377 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: Hounslow | Statement: [historic county of Middlesex, containedSettlement, Hounslow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hounslow
Context triple: [historic county of Middlesex, containedSettlement, Hounslow]
  • A. Hounslow chosen
    Hounslow is a suburban district in West London known for its diverse community, major transport links, and proximity to Heathrow Airport.
  • B. Surbiton
    Surbiton is a suburban area in southwest London, England, known for its commuter links to central London and its leafy residential character.
  • C. Hillingdon
    Hillingdon is a suburban borough in West London, England, known for containing Heathrow Airport and a mix of residential areas, green spaces, and commercial hubs.
  • D. Purley
    Purley is a suburban town in South London known for its residential character and location within the London Borough of Croydon.
  • E. Teddington
    Teddington is a suburban town in southwest London, England, known for its riverside location on the Thames and proximity to several royal parks.
  • 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_69aed933bec881909edfa28ebb69c634 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefba878a48190a2e234d775215938 completed March 9, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c2437136f48190b34454ce77397daf completed March 24, 2026, 7:55 a.m.
Created at: March 9, 2026, 3:37 p.m.