Triple

T7728776
Position Surface form Disambiguated ID Type / Status
Subject Henry Young Darracott Scott E175197 entity
Predicate workLocation P7 FINISHED
Object South Kensington E313026 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: South Kensington | Statement: [Henry Young Darracott Scott, workLocation, South Kensington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: South Kensington
Context triple: [Henry Young Darracott Scott, workLocation, South Kensington]
  • A. South Kensington chosen
    South Kensington is a London Underground station in West London, known for serving the museum district including the Natural History Museum, Science Museum, and Victoria and Albert Museum.
  • B. Kensington
    Kensington is a district in West London, England, known for its affluent residential areas, cultural institutions, and royal associations.
  • C. Kensington
    Kensington is a small, affluent residential village located on the North Shore of Long Island in Nassau County, New York.
  • D. Kensington
    Kensington is a small, affluent unincorporated community in Contra Costa County, California, located in the San Francisco Bay Area.
  • E. Kensington
    Kensington is a popular inner-city district in Calgary known for its vibrant mix of shops, restaurants, and cultural venues.
  • 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_69c6995e912c81909a49a2657103f786 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c703170650819095a1b073d67d231d completed March 27, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8c7c12e0081908eb984ba9bc558ff completed March 29, 2026, 6:33 a.m.
Created at: March 27, 2026, 4:06 p.m.