Triple
T3525980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yeovil |
E74538
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Yeovilton |
E340478
|
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: Yeovilton | Statement: [Yeovil, near, Yeovilton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yeovilton Context triple: [Yeovil, near, Yeovilton]
-
A.
Yeovilton
chosen
Yeovilton is a village in Somerset, England, best known for its Royal Naval Air Station and strong association with British naval aviation.
-
B.
Verwood
Verwood is a small town in eastern Dorset, England, known for its rural character and proximity to the New Forest and Cranborne Chase.
-
C.
Nailsea
Nailsea is a small town in North Somerset, England, historically known for its glassmaking and coal mining industries.
-
D.
Torquay
Torquay is a seaside resort town on the English Riviera in Devon, England, known for its mild climate, beaches, and Victorian-era tourism.
-
E.
Yeovil
Yeovil is a town in Somerset, England, known historically for its aircraft and defence industries and serving as a commercial and service hub for the surrounding rural area.
- 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_69ad85d0c5488190a3d8e02ebd01a1aa |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc6a8d0c819094d38b9c47fb67b4 |
completed | March 8, 2026, 6:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38bca41a88190b5550b9c1e763092 |
completed | March 13, 2026, 4 a.m. |
Created at: March 8, 2026, 3:19 p.m.