Triple
T28408757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jodrell Professor of Physiology at University College London |
E719608
|
entity |
| Predicate | associatedNobelLaureate |
P9522
|
FINISHED |
| Object | Andrew Huxley |
—
|
NE NERFINISHED |
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: Andrew Huxley | Statement: [Jodrell Professor of Physiology at University College London, associatedNobelLaureate, Andrew Huxley]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedNobelLaureate Context triple: [Jodrell Professor of Physiology at University College London, associatedNobelLaureate, Andrew Huxley]
-
A.
NobelPrizeCoLaureate
Indicates that two or more individuals share the same Nobel Prize as co-recipients for a particular award and year.
-
B.
namedForNobelLaureate
Indicates that one entity bears a name derived from or in honor of a Nobel Prize laureate.
-
C.
authorNobelLaureate
Indicates that the author is a recipient of a Nobel Prize.
-
D.
alumnusNobelLaureate
Indicates that the person is both an alumnus of a given institution and a recipient of a Nobel Prize.
-
E.
nobelPrizeRelated
chosen
Indicates that there is a connection or association between an entity and the Nobel Prize, such as receiving, being nominated for, or otherwise being significantly linked to it.
- F. None of above.
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_69eff6f0f37c8190b37bc6fab08a9449 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_6a013f09b0988190ba3179c7d56c726a |
completed | May 11, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_6a013e600e248190a1a9c363702c8586 |
completed | May 11, 2026, 2:26 a.m. |
Created at: April 28, 2026, 1:25 a.m.