Triple
T12405899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fifield |
E296384
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Holyport |
E296383
|
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: Holyport | Statement: [Fifield, near, Holyport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Holyport Context triple: [Fifield, near, Holyport]
-
A.
Holyport
chosen
Holyport is a village in Berkshire, England, known for its traditional green, historic pubs, and proximity to the towns of Windsor and Maidenhead.
-
B.
Bridport
Bridport is a historic market town in southwest England known for its rope-making heritage and proximity to the Jurassic Coast.
-
C.
Stourmouth
Stourmouth is a small rural village in Kent, England, situated near the River Stour and known for its historic church and countryside setting.
-
D.
Nailsea
Nailsea is a small town in North Somerset, England, historically known for its glassmaking and coal mining industries.
-
E.
Harleston
Harleston is a small market town in Norfolk, England, known for its historic architecture and rural surroundings.
- 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_69d6ad9f464c81909db36d7e96e34b9e |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d48f1908190918551c794f98fe3 |
completed | April 10, 2026, 7:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a533a2788190b885c000c29f4e87 |
completed | May 3, 2026, 1:30 a.m. |
Created at: April 8, 2026, 9:55 p.m.