Triple
T18829661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cambridge and County High School for Boys |
E460488
|
entity |
| Predicate | alumnusNobelPrizeField |
P133564
|
FINISHED |
| Object | Physiology or Medicine |
—
|
LITERAL 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: Physiology or Medicine | Statement: [Cambridge and County High School for Boys, alumnusNobelPrizeField, Physiology or Medicine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alumnusNobelPrizeField Context triple: [Cambridge and County High School for Boys, alumnusNobelPrizeField, Physiology or Medicine]
-
A.
NobelPrizeCoLaureate
Indicates that two or more individuals share the same Nobel Prize as co-recipients for a particular award and year.
-
B.
authorNobelLaureate
Indicates that the author is a recipient of a Nobel Prize.
-
C.
hasLaureate
Indicates that an entity (such as an award or prize) has a specific person or group as its laureate or recipient.
-
D.
authorNobelYear
Indicates the year in which an author received a Nobel Prize.
-
E.
roleInNobelPrize
Indicates the specific capacity or function an entity had in relation to a particular Nobel Prize (e.g., laureate, nominee, organization, or associated role).
- F. None of above. chosen
Provenance (4 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_69d8dcf94c288190a06dea029ae4b223 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a9981be88190b709c0e72ad3f7e6 |
completed | April 20, 2026, 4:20 a.m. |
| PD | Predicate disambiguation | batch_69e48d1b10ec8190985c6fb5766ff981 |
completed | April 19, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e49a9bcc0c81908df3e513fd6762ff |
completed | April 19, 2026, 9:04 a.m. |
Created at: April 10, 2026, 11:56 a.m.