Triple
T18611324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Harsent |
E454900
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Devizes |
—
|
NE NERFINISHED |
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: Devizes | Statement: [David Harsent, placeOfBirth, Devizes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Devizes Context triple: [David Harsent, placeOfBirth, Devizes]
-
A.
Devizes
chosen
Devizes is a historic market town and civil parish in Wiltshire, England, known for its medieval origins and well-preserved architecture.
-
B.
Leintwardine
Leintwardine is a small historic village in Herefordshire, England, near the Welsh border, known for its Roman heritage and rural setting.
-
C.
Villevere
Villevere is a small village located in Järva County in central Estonia.
-
D.
Glanville
Glanville is a surname most prominently associated with Jerry Glanville, an American football coach and former NFL head coach known for his flamboyant personality and aggressive defensive style.
-
E.
Grosmont
Grosmont is a historic village in Monmouthshire, Wales, known for its medieval castle and picturesque rural setting near the Welsh–English border.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38bbe7c8190bdec3138e7d413c9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54d013748819099126e27e7ec543d |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 10, 2026, 11:45 a.m.