Triple
T7368345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denmark Hill |
E169926
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Peckham |
E164254
|
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: Peckham | Statement: [Denmark Hill, near, Peckham]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peckham Context triple: [Denmark Hill, near, Peckham]
-
A.
Peckham
chosen
Peckham is a vibrant, multicultural district in south London known for its lively arts scene, markets, and diverse community.
-
B.
Brixton
Brixton is a vibrant district in south London known for its multicultural community, lively markets, music scene, and significant role in Black British culture.
-
C.
Crouch End
Crouch End is a leafy, affluent residential district in north London known for its village-like atmosphere, independent shops, and vibrant arts and café culture.
-
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.
Southall
Southall is a suburban district in West London, England, known for its large South Asian community and vibrant multicultural atmosphere.
- 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_69c68a5ade988190885b7175f63b7534 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f17fe278819094eb1dd886583c6a |
completed | March 27, 2026, 9:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8de96d58c819086c308396a4a304e |
completed | March 29, 2026, 8:11 a.m. |
Created at: March 27, 2026, 3:07 p.m.