Triple
T1814231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cherwell |
E40399
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Bicester |
E39224
|
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: Bicester | Statement: [Cherwell, hasTown, Bicester]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bicester Context triple: [Cherwell, hasTown, Bicester]
-
A.
Bicester
chosen
Bicester is a historic market town in Oxfordshire, England, best known today for its rapid growth and the popular designer outlet shopping destination Bicester Village.
-
B.
Banbury
Banbury is a historic market town in Oxfordshire, England, known for its medieval cross, canal-side setting, and association with the traditional Banbury cake.
-
C.
Wantage
Wantage is a historic market town in Oxfordshire, England, best known as the birthplace of King Alfred the Great.
-
D.
Aylesbury
Aylesbury is a historic market town in southern England that serves as an important commercial and administrative center in Buckinghamshire.
-
E.
Didcot
Didcot is a town in Oxfordshire, England, known historically for its railway junction and nearby power stations.
- 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_69a8864526c081908a3a4d74f689e2c5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa65c905ec8190bea7cd72d218487a |
completed | March 6, 2026, 5:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afbba693f08190aead3b593f081c62 |
completed | March 10, 2026, 6:35 a.m. |
Created at: March 4, 2026, 7:32 p.m.