Triple
T11289381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Newton |
E267283
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Newton |
E257267
|
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: Newton | Statement: [Tony Newton, familyName, Newton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Newton Context triple: [Tony Newton, familyName, Newton]
-
A.
Newton
Newton is a small settlement in West Lothian, Scotland, known primarily as a residential village within the Edinburgh commuter belt.
-
B.
Newton
Newton is a suburban city in Massachusetts known for its residential neighborhoods, strong public schools, and proximity to Boston.
-
C.
Newton
chosen
Newton is a common English surname most famously associated with figures such as physicist Sir Isaac Newton and activist Huey P. Newton.
-
D.
Newton
Newton is a small Midwestern town that later became known as Rensselaer in Indiana, United States.
-
E.
Newton
Newton is a small city in central Iowa known historically for its manufacturing industry, particularly as the former headquarters of the Maytag Corporation.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e98875a08190b8509fe55e49d52d |
completed | April 9, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4f49badc88190a3195e919900f0c3 |
completed | April 19, 2026, 3:28 p.m. |
Created at: April 8, 2026, 9:32 p.m.