Triple
T456926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sydney Camm |
E7252
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Surrey |
E2921
|
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: Surrey | Statement: [Sydney Camm, workLocation, Surrey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Surrey Context triple: [Sydney Camm, workLocation, Surrey]
-
A.
Surrey
chosen
Surrey is a county in southeast England known for its historic towns, affluent suburbs, and proximity to London.
-
B.
Buckinghamshire
Buckinghamshire is a ceremonial and non-metropolitan county in South East England, known for its historic towns, Chiltern Hills countryside, and proximity to London.
-
C.
West Sussex
West Sussex is a county in South East England known for its mix of coastal towns, rural countryside, and historic market settlements.
-
D.
Sussex
Sussex is a traditional British dual-purpose chicken breed valued for both its meat and egg production.
-
E.
Essex
Essex is a county in the east of England, known for its mix of rural landscapes, historic towns, and proximity to London.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efa1616481909399f92551a0c9e3 |
completed | Feb. 28, 2026, 1:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a6732881488190a6f6eb556a42277c |
completed | March 3, 2026, 5:35 a.m. |
Created at: Feb. 28, 2026, 1:12 p.m.