Triple
T277553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OX |
E5280
|
entity |
| Predicate | hasPostTown |
P2711
|
FINISHED |
| Object |
Didcot
Didcot is a town in Oxfordshire, England, known historically for its railway junction and nearby power stations.
|
E40398
|
NE FINISHED |
How this triple was built (4 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: Didcot | Statement: [OX, hasPostTown, Didcot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Didcot Context triple: [OX, hasPostTown, Didcot]
-
A.
Bicester
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.
Chipping Norton
Chipping Norton is a historic market town in Oxfordshire, England, known for its Cotswold stone architecture and rural surroundings.
-
D.
Farnham
Farnham is a historic market town in southern England known for its Georgian streets, medieval castle, and surrounding Surrey countryside.
-
E.
Camberley
Camberley is a suburban town in southeast England known for its shopping centre, commuter links to London, and proximity to the Royal Military Academy Sandhurst.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Didcot Triple: [OX, hasPostTown, Didcot]
Generated description
Didcot is a town in Oxfordshire, England, known historically for its railway junction and nearby power stations.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Didcot Target entity description: Didcot is a town in Oxfordshire, England, known historically for its railway junction and nearby power stations.
-
A.
Bicester
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.
Chipping Norton
Chipping Norton is a historic market town in Oxfordshire, England, known for its Cotswold stone architecture and rural surroundings.
-
D.
Farnham
Farnham is a historic market town in southern England known for its Georgian streets, medieval castle, and surrounding Surrey countryside.
-
E.
Camberley
Camberley is a suburban town in southeast England known for its shopping centre, commuter links to London, and proximity to the Royal Military Academy Sandhurst.
- F. None of above. chosen
Provenance (5 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25ded68c88190b1fc595ce329aeb9 |
completed | Feb. 28, 2026, 3:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3c4141d288190a6873cf20e360fe1 |
completed | March 1, 2026, 4:44 a.m. |
| NEDg | Description generation | batch_69a3c47e0cb081909e1b2534d47bc6b0 |
completed | March 1, 2026, 4:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3c4cbb00481909f4e3f77b74a1d33 |
completed | March 1, 2026, 4:47 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.