Triple
T16534008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raynham |
E401640
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Norton |
E155744
|
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: Norton | Statement: [Raynham, borders, Norton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norton Context triple: [Raynham, borders, Norton]
-
A.
Norton
Norton is a town within the Teesside urban area in North East England, known for its historic high street and village green.
-
B.
Norton
Norton is a surname of English origin borne by numerous notable individuals across fields such as literature, politics, and the arts.
-
C.
Norton
Norton is a dark-skinned American grape variety, historically significant in Midwestern and Eastern U.S. winemaking for producing deeply colored, full-bodied red wines with notable disease resistance.
-
D.
Norton
Norton is a village in Gloucestershire, England, situated near the River Chelt and close to the town of Cheltenham.
-
E.
Norton
chosen
Norton is a small town in Bristol County, southeastern Massachusetts, known for being home to Wheaton College and several scenic ponds and conservation areas.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32eda42548190be61efb25a44a554 |
completed | April 18, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006093244081909ae74674de966d6d |
completed | May 10, 2026, 10:40 a.m. |
Created at: April 10, 2026, 5:15 a.m.