Triple
T5996693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Norton |
E133487
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Norton |
E89028
|
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: [Peter Norton, hasFamilyName, Norton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norton Context triple: [Peter Norton, hasFamilyName, Norton]
-
A.
Norton
chosen
Norton is a surname of English origin borne by numerous notable individuals across fields such as literature, politics, and the arts.
-
B.
Norton
Norton is a small town in Bristol County, southeastern Massachusetts, known for being home to Wheaton College and several scenic ponds and conservation areas.
-
C.
Norton
Norton is a historic British motorcycle manufacturer renowned for its success in mid-20th-century road racing and the Isle of Man TT.
-
D.
Norton
Norton is a residential suburb within the town of Runcorn in Cheshire, England.
-
E.
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.
- 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_69c00870ddbc81909880fa3864f4f38d |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04e963f3c819082dd755e328ab947 |
completed | March 22, 2026, 8:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c10876d4d0819083ac7431c8abaedd |
completed | March 23, 2026, 9:31 a.m. |
Created at: March 22, 2026, 4:05 p.m.