Triple
T3364505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Nurse |
E70802
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Paul Nurse |
E70802
|
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: Paul Nurse | Statement: [Paul Nurse, name, Paul Nurse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paul Nurse Context triple: [Paul Nurse, name, Paul Nurse]
-
A.
Paul Nurse
chosen
Paul Nurse is a British geneticist and cell biologist, Nobel Prize laureate, and former president of the Royal Society known for his pioneering work on cell cycle regulation.
-
B.
Robin Driscoll
Robin Driscoll is a British comedy writer and actor best known for co-writing and shaping the character and television series of Mr. Bean.
-
C.
Pat Hughes
Pat Hughes is a longtime American sportscaster best known as the radio play-by-play voice of Major League Baseball’s Chicago Cubs.
-
D.
Nel Wright
Nel Wright is a central character in Toni Morrison's novel "Sula," known for her complex, lifelong friendship with the title character and her struggle with identity, loyalty, and moral judgment.
-
E.
Gil Robbins
Gil Robbins was an American folk musician and actor, best known as a member of the Highwaymen and for his work in the 1960s folk scene.
- 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_69ad85a729d48190afd789cd8417f289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb28467b88190bdf70b851bc8efa9 |
completed | March 8, 2026, 5:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3254daf8c8190b2141682503c111e |
completed | March 12, 2026, 8:42 p.m. |
Created at: March 8, 2026, 3:13 p.m.