Triple
T4067942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kelmscott |
E86371
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Faringdon |
E212397
|
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: Faringdon | Statement: [Kelmscott, locatedNear, Faringdon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Faringdon Context triple: [Kelmscott, locatedNear, Faringdon]
-
A.
Faringdon
chosen
Faringdon is a historic market town in Oxfordshire, England, known for its medieval church, traditional market square, and nearby Faringdon Folly tower.
-
B.
Stonesfield
Stonesfield is a rural village in Oxfordshire, England, known historically for its Cotswold stone quarries and scenic countryside setting.
-
C.
Freckenham
Freckenham is a small rural village and civil parish located in the English county of Suffolk.
-
D.
Farningham
Farningham is a historic village in the Sevenoaks District of Kent, England, known for its rural character and location on the River Darent.
-
E.
Fairford
Fairford is a small market town in Gloucestershire, England, known for its historic wool church and proximity to RAF Fairford airbase.
- 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_69aed93c69208190a4efac0efe3cd69b |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefbf8f33c8190a6afca1830f35485 |
completed | March 9, 2026, 4:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56b55b5388190a90551c43388f3fc |
completed | March 14, 2026, 2:06 p.m. |
Created at: March 9, 2026, 3:38 p.m.