Triple
T4849461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Selhurst Park |
E108375
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object |
Selhurst
Selhurst is a residential district in the London Borough of Croydon, best known for being home to Crystal Palace Football Club’s stadium, Selhurst Park.
|
E642490
|
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: Selhurst | Statement: [Selhurst Park, location, Selhurst]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Selhurst Context triple: [Selhurst Park, location, Selhurst]
-
A.
Surbiton
Surbiton is a suburban area in southwest London, England, known for its commuter links to central London and its leafy residential character.
-
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.
Kentish Town
Kentish Town is a residential and commercial district in north London known for its vibrant high street, music venues, and proximity to central London.
-
D.
Willesden
Willesden is a residential district in the London Borough of Brent, known for its diverse community and good transport links in northwest London.
-
E.
Hounslow
Hounslow is a suburban district in West London known for its diverse community, major transport links, and proximity to Heathrow Airport.
- 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: Selhurst Triple: [Selhurst Park, location, Selhurst]
Generated description
Selhurst is a residential district in the London Borough of Croydon, best known for being home to Crystal Palace Football Club’s stadium, Selhurst Park.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Selhurst Target entity description: Selhurst is a residential district in the London Borough of Croydon, best known for being home to Crystal Palace Football Club’s stadium, Selhurst Park.
-
A.
Surbiton
Surbiton is a suburban area in southwest London, England, known for its commuter links to central London and its leafy residential character.
-
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.
Kentish Town
Kentish Town is a residential and commercial district in north London known for its vibrant high street, music venues, and proximity to central London.
-
D.
Willesden
Willesden is a residential district in the London Borough of Brent, known for its diverse community and good transport links in northwest London.
-
E.
Hounslow
Hounslow is a suburban district in West London known for its diverse community, major transport links, and proximity to Heathrow Airport.
- 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_69bd4409b264819085ab855f3eb5381a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d1e5cf08190bd6b6a524748f170 |
completed | March 20, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79c6a0fdc8190be37008d4f036e51 |
completed | March 28, 2026, 9:16 a.m. |
| NEDg | Description generation | batch_69c79e48056081909eac95bf6ebdb209 |
completed | March 28, 2026, 9:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c79f0b2a6c819091a2d72942f8f8c5 |
completed | March 28, 2026, 9:27 a.m. |
Created at: March 20, 2026, 1:25 p.m.