Triple
T8152175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Écuries d’Augias |
E190357
|
entity |
| Predicate | authorIsFirstNobelLaureateInLiterature |
P80840
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Les Écuries d’Augias, authorIsFirstNobelLaureateInLiterature, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: authorIsFirstNobelLaureateInLiterature Context triple: [Les Écuries d’Augias, authorIsFirstNobelLaureateInLiterature, true]
-
A.
writtenByNobelLaureate
Indicates that the work or document was authored by a person who has received a Nobel Prize.
-
B.
authorNobelYear
Indicates the year in which an author received a Nobel Prize.
-
C.
NobelPrizeCoLaureate
Indicates that two or more individuals share the same Nobel Prize as co-recipients for a particular award and year.
-
D.
siblingOfNobelLaureateInLiterature
Indicates a person who is the sibling of an individual who has received the Nobel Prize in Literature.
-
E.
literaryAuthor
Indicates that one entity is the author or writer of a literary work represented by the other entity.
- 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_69ca82be7ba8819087de0147e9292c83 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4483799c81908e73f9a87ed99185 |
completed | March 31, 2026, 3:50 a.m. |
| PD | Predicate disambiguation | batch_69cb36a0847c8190af9038aef78319b3 |
completed | March 31, 2026, 2:51 a.m. |
| PDg | Predicate description generation | batch_69cb39ba412881908a053e88f29a9588 |
completed | March 31, 2026, 3:04 a.m. |
Created at: March 30, 2026, 5:37 p.m.