Triple
T17102782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingham railway station |
E415019
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Kingham |
E92756
|
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: Kingham | Statement: [Kingham railway station, serves, Kingham]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kingham Context triple: [Kingham railway station, serves, Kingham]
-
A.
Kingham
chosen
Kingham is a picturesque rural village in the Cotswolds area of Oxfordshire, England, known for its traditional stone cottages and countryside setting.
-
B.
Warmingham
Warmingham is a small rural village in Cheshire, England, known for its historic church and tranquil countryside setting.
-
C.
Coningham
Coningham is an English-language surname borne by several notable figures, including military officers and politicians.
-
D.
Cretingham
Cretingham is a small rural village and civil parish in the English county of Suffolk, known for its historic church and countryside setting.
-
E.
Kilnsey
Kilnsey is a small rural village in the Yorkshire Dales of northern England, known for its dramatic limestone crag and scenic countryside.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc2495c88190b5b16a006a994faf |
completed | April 18, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0139ffbe808190a24e827331ee4a6c |
completed | May 11, 2026, 2:07 a.m. |
Created at: April 10, 2026, 5:35 a.m.