Triple
T4495260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cricklewood |
E100678
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object |
Willesden
Willesden is a residential district in the London Borough of Brent, known for its diverse community and good transport links in northwest London.
|
E598609
|
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: Willesden | Statement: [Cricklewood, near, Willesden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Willesden Context triple: [Cricklewood, near, Willesden]
-
A.
Harlesden
Harlesden is a residential district in northwest London known for its diverse community and strong Caribbean and Brazilian cultural influences.
-
B.
Wood Green
Wood Green is a busy urban district and major shopping and transport hub in the London Borough of Haringey in north London.
-
C.
Surbiton
Surbiton is a suburban area in southwest London, England, known for its commuter links to central London and its leafy residential character.
-
D.
Hammersmith
Hammersmith is a district in West London known as a major commercial and transport hub along the River Thames.
-
E.
Edgware
Edgware is a suburban district in north London known for its residential character, shopping facilities, and role as a transport hub on the London Underground.
- 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: Willesden Triple: [Cricklewood, near, Willesden]
Generated description
Willesden is a residential district in the London Borough of Brent, known for its diverse community and good transport links in northwest London.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Willesden Target entity description: Willesden is a residential district in the London Borough of Brent, known for its diverse community and good transport links in northwest London.
-
A.
Harlesden
Harlesden is a residential district in northwest London known for its diverse community and strong Caribbean and Brazilian cultural influences.
-
B.
Wood Green
Wood Green is a busy urban district and major shopping and transport hub in the London Borough of Haringey in north London.
-
C.
Surbiton
Surbiton is a suburban area in southwest London, England, known for its commuter links to central London and its leafy residential character.
-
D.
Hammersmith
Hammersmith is a district in West London known as a major commercial and transport hub along the River Thames.
-
E.
Edgware
Edgware is a suburban district in north London known for its residential character, shopping facilities, and role as a transport hub on the London Underground.
- F. None of above. chosen
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_69bd43cdf15081909a4fa2585ff63b3e |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd56bde14c819091d42839a46291d0 |
completed | March 20, 2026, 2:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c67c2b4f188190a78b591674040060 |
completed | March 27, 2026, 12:46 p.m. |
| NEDg | Description generation | batch_69c67da1278c8190b75f7adc5f52795a |
completed | March 27, 2026, 12:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c67dfc51048190adeccd569c85da85 |
completed | March 27, 2026, 12:54 p.m. |
Created at: March 20, 2026, 1 p.m.