Triple
T18373413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brent Central |
E446245
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Willesden |
—
|
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: Willesden | Statement: [Brent Central, contains, Willesden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Willesden Context triple: [Brent Central, contains, Willesden]
-
A.
Willesden
chosen
Willesden is a residential district in the London Borough of Brent, known for its diverse community and good transport links in northwest London.
-
B.
Harlesden
Harlesden is a residential district in northwest London known for its diverse community and strong Caribbean and Brazilian cultural influences.
-
C.
Perivale
Perivale is a suburban area in the London Borough of Ealing, known for its residential neighborhoods, industrial estates, and green spaces in west London.
-
D.
Wood Green
Wood Green is a busy urban district and major shopping and transport hub in the London Borough of Haringey in north London.
-
E.
Yiewsley
Yiewsley is a suburban area in the London Borough of Hillingdon in west London, known for its residential character and proximity to waterways and transport links.
- 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_69d8b9f370b88190b1e5081c2c238e7f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e517561edc8190b5d2834707ab662b |
completed | April 19, 2026, 5:56 p.m. |
Created at: April 10, 2026, 10:45 a.m.