Triple

T15593547
Position Surface form Disambiguated ID Type / Status
Subject Royal Garden Hotel E374809 entity
Predicate neighbourhood P988 FINISHED
Object Kensington E14419 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: Kensington | Statement: [Royal Garden Hotel, neighbourhood, Kensington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kensington
Context triple: [Royal Garden Hotel, neighbourhood, Kensington]
  • A. Kensington chosen
    Kensington is a district in West London, England, known for its affluent residential areas, cultural institutions, and royal associations.
  • B. Kensington
    Kensington is an inner-city suburb of Sydney, Australia, known for hosting the main campus of the University of New South Wales.
  • 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 an inner-city suburb of Melbourne, Victoria, known for its mix of historic workers’ cottages, industrial heritage, and growing residential developments close to the central business district.
  • E. Kensington
    Kensington is a residential suburb within the City of Swan in Western Australia, known for its local community amenities and proximity to Perth’s urban areas.
  • 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_69d85cce25008190b13b52745fbd719b completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e5e43d48190a8fd367f13f1c7e1 completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a001799fbac8190b75a48a8c63e3381 completed May 10, 2026, 5:28 a.m.
Created at: April 10, 2026, 4:12 a.m.