Triple
T14206950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen's Park |
E352118
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Kilburn |
E398550
|
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: Kilburn | Statement: [Queen's Park, near, Kilburn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kilburn Context triple: [Queen's Park, near, Kilburn]
-
A.
Kilburn
chosen
Kilburn is a diverse residential and commercial district in northwest London known for its vibrant high street and strong Irish and Afro-Caribbean communities.
-
B.
North Kensington
North Kensington is a residential and culturally diverse area in west London known for its strong community identity and proximity to Notting Hill and Ladbroke Grove.
-
C.
Wood Green
Wood Green is a busy urban district and major shopping and transport hub in the London Borough of Haringey in north London.
-
D.
Handsworth
Handsworth is a suburban area of Birmingham, England, historically significant for its role in the Industrial Revolution and as the home of industrialist Matthew Boulton.
-
E.
Harlesden
Harlesden is a residential district in northwest London known for its diverse community and strong Caribbean and Brazilian cultural influences.
- 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_69d827894ac0819097803e57f3227b23 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61f84f288190877116330bd54393 |
completed | April 14, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d0a172c819096874f1bdd290cbb |
completed | May 8, 2026, 1:31 a.m. |
Created at: April 10, 2026, 1:05 a.m.