Triple

T5265375
Position Surface form Disambiguated ID Type / Status
Subject Windsor Terrace E118925 entity
Predicate borderedBy P224 FINISHED
Object Kensington
Kensington is a residential neighborhood in central Brooklyn, New York City, known for its diverse population and mix of apartment buildings and single-family homes.
 E475671 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: [Windsor Terrace, borderedBy, Kensington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kensington
Context triple: [Windsor Terrace, borderedBy, 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. Kensington
    Kensington is a historic Philadelphia neighborhood known for its industrial past and ongoing urban redevelopment.
  • E. Kensington
    Kensington is an inner-city suburb of Sydney, Australia, known for hosting the main campus of the University of New South Wales.
  • 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: [Windsor Terrace, borderedBy, Kensington]
Generated description
Kensington is a residential neighborhood in central Brooklyn, New York City, known for its diverse population and mix of apartment buildings and single-family homes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kensington
Target entity description: Kensington is a residential neighborhood in central Brooklyn, New York City, known for its diverse population and mix of apartment buildings and single-family homes.
  • A. Kensington chosen
    Kensington is a residential neighborhood in central Brooklyn, New York City, known for its diverse population and mix of apartment buildings and single-family homes.
  • 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 historic Philadelphia neighborhood known for its industrial past and ongoing urban redevelopment.
  • 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.

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_69bd446a42c88190b7ecbef006561d55 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7bf89ae481908835b711fb2696fd completed March 20, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf7fcb783881909cc693e4832a19e3 completed March 22, 2026, 5:36 a.m.
NEDg Description generation batch_69bf804be0f881908f990e40478ff2d9 completed March 22, 2026, 5:38 a.m.
NED2 Entity disambiguation (via description) batch_69bf809da5288190a0f83f4b877eeaab completed March 22, 2026, 5:39 a.m.
Created at: March 20, 2026, 1:51 p.m.