Triple
T5924573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nigel Shadbolt |
E131774
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Nigel Shadbolt |
E131774
|
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: Nigel Shadbolt | Statement: [Nigel Shadbolt, name, Nigel Shadbolt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nigel Shadbolt Context triple: [Nigel Shadbolt, name, Nigel Shadbolt]
-
A.
Nigel Shadbolt
chosen
Nigel Shadbolt is a British computer scientist and artificial intelligence researcher known for his leading role in promoting open data and digital governance.
-
B.
Nigel Sears
Nigel Sears is a British tennis coach best known for working with several top WTA players, including former world No. 1 Ana Ivanovic.
-
C.
Graham Dumpleton
Graham Dumpleton is a software engineer and open-source developer best known for creating and maintaining mod_wsgi, a popular Apache module for hosting Python web applications.
-
D.
Douglas Slocombe
Douglas Slocombe was a renowned British cinematographer celebrated for his work on numerous classic films, including major entries in the Indiana Jones series.
-
E.
Peter Sargeant
Peter Sargeant was a colonial-era jurist who served as a judge on the Court of Oyer and Terminer.
- 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_69c0085a1ed08190a7e9a8b6323fd680 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03852806c81908ba726c16adf3358 |
completed | March 22, 2026, 6:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0e3a9b6348190909e14e095e2eea0 |
completed | March 23, 2026, 6:54 a.m. |
Created at: March 22, 2026, 4 p.m.