Triple
T3293883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A4 road |
E69163
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Marlborough |
E211708
|
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: Marlborough | Statement: [A4 road, passesThrough, Marlborough]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marlborough Context triple: [A4 road, passesThrough, Marlborough]
-
A.
Marlborough
chosen
Marlborough is a historic market town in Wiltshire, England, known for its broad High Street and well-preserved architecture.
-
B.
Marlborough
Marlborough is a small New England town in central Connecticut known for its rural character and residential communities.
-
C.
Marlborough
Marlborough is a renowned wine-producing region in New Zealand, celebrated especially for its high-quality cool-climate varietals.
-
D.
Wilton
Wilton is a town in Saratoga County, New York, known for its suburban communities, commercial development, and proximity to Saratoga Springs.
-
E.
Wilton
Wilton was a former UK parliamentary constituency in Wiltshire, historically represented in the House of Commons before its abolition in the 19th century.
- 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_69ad859d45748190b0742408c954b39f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb074f35081909dd3c8a09544b5f1 |
completed | March 8, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3cfec98819094208d2cb6e459ea |
completed | March 12, 2026, 5:11 p.m. |
Created at: March 8, 2026, 3:10 p.m.