Triple

T1493572
Position Surface form Disambiguated ID Type / Status
Subject Science Museum, London E29636 entity
Predicate locatedIn P40 FINISHED
Object South Kensington
South Kensington is a district in West London known for its concentration of major museums, cultural institutions, and affluent residential areas.
 E14419 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: South Kensington | Statement: [Science Museum, London, locatedIn, South Kensington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: South Kensington
Context triple: [Science Museum, London, locatedIn, South 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. Roehampton
    Roehampton is a suburban district in southwest London, England, known for its large housing estates, green spaces, and the University of Roehampton.
  • E. Camberwell
    Camberwell is a district in south London known for its diverse community, vibrant arts scene, and mix of historic and modern urban character.
  • 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: South Kensington
Triple: [Science Museum, London, locatedIn, South Kensington]
Generated description
South Kensington is a district in West London known for its concentration of major museums, cultural institutions, and affluent residential areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: South Kensington
Target entity description: South Kensington is a district in West London known for its concentration of major museums, cultural institutions, and affluent residential areas.
  • 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 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. Roehampton
    Roehampton is a suburban district in southwest London, England, known for its large housing estates, green spaces, and the University of Roehampton.
  • E. Camberwell
    Camberwell is a district in south London known for its diverse community, vibrant arts scene, and mix of historic and modern urban character.
  • 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_69a498dba1d8819093b46a3a8d2485f1 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c6c665488190ae665f7a1b0563f5 completed March 1, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69adfb8d636c8190a8a9ca29d8a6fd82 completed March 8, 2026, 10:43 p.m.
NEDg Description generation batch_69adfc9a4060819085d69a8642e49673 completed March 8, 2026, 10:47 p.m.
NED2 Entity disambiguation (via description) batch_69adfd03414c8190b1fc2b5608563726 completed March 8, 2026, 10:49 p.m.
Created at: March 1, 2026, 8:12 p.m.