Triple

T11256676
Position Surface form Disambiguated ID Type / Status
Subject Diane Abbott E266454 entity
Predicate residence P75 FINISHED
Object Hackney E143459 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: Hackney | Statement: [Diane Abbott, residence, Hackney]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hackney
Context triple: [Diane Abbott, residence, Hackney]
  • A. Hammersmith
    Hammersmith is a district in West London known as a major commercial and transport hub along the River Thames.
  • B. Southwark
    Southwark is a historic district in central London on the south bank of the River Thames, known for landmarks such as Borough Market, The Shard, and Shakespeare’s Globe.
  • C. Islington
    Islington is a vibrant inner London borough in England known for its dense urban character, cultural venues, and strong football heritage.
  • D. Islington
    Islington is a village within the town of Westwood, Massachusetts, known as one of its primary residential neighborhoods.
  • E. London Borough of Hackney chosen
    The London Borough of Hackney is an inner London borough in East London known for its diverse communities, vibrant arts and nightlife scenes, and rapid urban regeneration.
  • 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_69d6aac7953c8190b82caf9d7640fdf9 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e935b85c819085e1abf2dd4099c5 completed April 9, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69e58af8bc988190805168188ed0a6aa completed April 20, 2026, 2:10 a.m.
Created at: April 8, 2026, 9:31 p.m.