Triple
T18661251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jimmy Sangster |
E456201
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Kensington |
—
|
NE NERFINISHED |
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: [Jimmy Sangster, placeOfBirth, Kensington]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kensington Context triple: [Jimmy Sangster, placeOfBirth, 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 a small, affluent unincorporated community in Contra Costa County, California, located in the San Francisco Bay Area.
-
C.
Kensington
Kensington is a historic Philadelphia neighborhood known for its industrial past and ongoing urban redevelopment.
-
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 (2 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_69d8d38f72b4819090a935175d9ca8af |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5508a30248190abdb51e345168849 |
completed | April 19, 2026, 10 p.m. |
Created at: April 10, 2026, 11:48 a.m.