Triple

T13248617
Position Surface form Disambiguated ID Type / Status
Subject Lower Sydenham E315469 entity
Predicate partOf P40 FINISHED
Object Sydenham E236913 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: Sydenham | Statement: [Lower Sydenham, partOf, Sydenham]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sydenham
Context triple: [Lower Sydenham, partOf, Sydenham]
  • A. Sydenham chosen
    Sydenham is a suburban district in southeast London, England, known for its Victorian architecture, green spaces, and residential character.
  • B. Sydenham
    Sydenham is the former name of the Canadian city now known as Owen Sound in Ontario.
  • C. Sydenham
    Sydenham is a district in east Belfast, Northern Ireland, known for its residential areas and proximity to key transport links including George Best Belfast City Airport.
  • D. Moorfield
    Moorfield is a given name most notably borne by Moorfield Storey, an American lawyer and civil rights leader who served as the first president of the NAACP.
  • E. Winster
    Winster is a historic village in England’s Peak District, known for its traditional stone houses, former lead-mining heritage, and well-preserved conservation area.
  • 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_69d806b1072881909e46bd212259c5f0 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d9e7ea881908abc4b3a54896692 completed April 10, 2026, 11:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff37f7448190b9c555cae010d3b6 completed May 3, 2026, 7:54 a.m.
Created at: April 9, 2026, 9:24 p.m.