Triple

T2241291
Position Surface form Disambiguated ID Type / Status
Subject University of New South Wales E49400 entity
Predicate campus P269 FINISHED
Object Kensington
Kensington is an inner-city suburb of Sydney, Australia, known for hosting the main campus of the University of New South Wales.
 E278476 NE FINISHED

How this triple was built (4 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: [University of New South Wales, campus, Kensington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kensington
Context triple: [University of New South Wales, campus, Kensington]
  • A. Kensington
    Kensington is a district in West London, England, known for its affluent residential areas, cultural institutions, and royal associations.
  • B. Kensington
    Kensington is a small, affluent unincorporated community in Contra Costa County, California, located in the San Francisco Bay Area.
  • C. Kensington
    Kensington is a popular inner-city district in Calgary known for its vibrant mix of shops, restaurants, and cultural venues.
  • D. Hampstead
    Hampstead is a historic and affluent district in north London, England, known for its literary and artistic associations and the expansive Hampstead Heath.
  • E. Hampstead
    Hampstead is a small, affluent residential town on the Island of Montreal in Quebec, Canada, known for its suburban character and tree-lined streets.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kensington
Triple: [University of New South Wales, campus, Kensington]
Generated description
Kensington is an inner-city suburb of Sydney, Australia, known for hosting the main campus of the University of New South Wales.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kensington
Target entity description: Kensington is an inner-city suburb of Sydney, Australia, known for hosting the main campus of the University of New South Wales.
  • A. Kensington
    Kensington is a district in West London, England, known for its affluent residential areas, cultural institutions, and royal associations.
  • B. Kensington
    Kensington is a small, affluent unincorporated community in Contra Costa County, California, located in the San Francisco Bay Area.
  • C. Kensington
    Kensington is a popular inner-city district in Calgary known for its vibrant mix of shops, restaurants, and cultural venues.
  • D. Hampstead
    Hampstead is a historic and affluent district in north London, England, known for its literary and artistic associations and the expansive Hampstead Heath.
  • E. Hampstead
    Hampstead is a small, affluent residential town on the Island of Montreal in Quebec, Canada, known for its suburban character and tree-lined streets.
  • F. None of above. chosen

Provenance (5 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_69a88aa979788190ad6500f1d8eee2fc completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc0be7fb4819081a5f9c46b616bdb completed March 7, 2026, 6:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69af65388fd48190995f778d6438f739 completed March 10, 2026, 12:26 a.m.
NEDg Description generation batch_69af65f16fc48190a8611279322dd936 completed March 10, 2026, 12:29 a.m.
NED2 Entity disambiguation (via description) batch_69af66613dc88190af6a0aa1108a9069 completed March 10, 2026, 12:31 a.m.
Created at: March 4, 2026, 7:47 p.m.