Triple

T4423293
Position Surface form Disambiguated ID Type / Status
Subject Daniel Radcliffe E95151 entity
Predicate placeOfBirth P1 FINISHED
Object Hammersmith E81474 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: Hammersmith | Statement: [Daniel Radcliffe, placeOfBirth, Hammersmith]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hammersmith
Context triple: [Daniel Radcliffe, placeOfBirth, Hammersmith]
  • A. Hammersmith chosen
    Hammersmith is a district in West London known as a major commercial and transport hub along the River Thames.
  • B. Harlesden
    Harlesden is a residential district in northwest London known for its diverse community and strong Caribbean and Brazilian cultural influences.
  • C. Kensington and Chelsea
    Kensington and Chelsea is a central-west London borough known for its affluent residential areas, cultural institutions, and landmarks such as Kensington Palace and the King's Road.
  • D. St John’s Wood
    St John’s Wood is an affluent residential district in northwest London, known for its tree-lined streets, elegant villas, and landmarks such as Lord’s Cricket Ground and Abbey Road.
  • E. Lambeth
    Lambeth is a central London borough on the south bank of the River Thames, known for landmarks such as the London Eye and its diverse urban communities.
  • 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_69b3453a36908190b95a79a297ca083c completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3554b36a48190a475ac5474bed132 completed March 13, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69bf06913b448190be47c002641abd34 completed March 21, 2026, 8:58 p.m.
Created at: March 12, 2026, 11:30 p.m.