Triple
T25123139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nothing Twice |
E629319
|
entity |
| Predicate | creatorNobelPrizeStatus |
P90396
|
FINISHED |
| Object | author is Nobel laureate in Literature |
—
|
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: author is Nobel laureate in Literature | Statement: [Nothing Twice, creatorNobelPrizeStatus, author is Nobel laureate in Literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: creatorNobelPrizeStatus Context triple: [Nothing Twice, creatorNobelPrizeStatus, author is Nobel laureate in Literature]
-
A.
NobelPrizeStatus
Indicates whether an entity has received, been nominated for, or otherwise holds a particular status related to the Nobel Prize.
-
B.
authorNobelLaureate
chosen
Indicates that the author is a recipient of a Nobel Prize.
-
C.
creatorNobelPrizeCategory
Indicates that a person is the creator or originator associated with a particular Nobel Prize category.
-
D.
NobelPrizeCoLaureate
Indicates that two or more individuals share the same Nobel Prize as co-recipients for a particular award and year.
-
E.
hasAuthorNobelEquivalent
Indicates that the author of the work has received an award considered equivalent in prestige or recognition to a Nobel Prize in their field.
- 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_69e2ff3288048190bd82c3b7f7bd0e62 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f6135293908190809e255bf6334760 |
completed | May 2, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_69f611a72780819082f44e66ca2c6ac9 |
completed | May 2, 2026, 3 p.m. |
Created at: April 18, 2026, 6:28 a.m.