Triple
T4414049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salam–Weinberg model |
E94919
|
entity |
| Predicate | NobelPrizeAssociated |
P9522
|
FINISHED |
| Object | 1979 Nobel Prize in Physics |
—
|
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: 1979 Nobel Prize in Physics | Statement: [Salam–Weinberg model, NobelPrizeAssociated, 1979 Nobel Prize in Physics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NobelPrizeAssociated Context triple: [Salam–Weinberg model, NobelPrizeAssociated, 1979 Nobel Prize in Physics]
-
A.
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.
-
B.
NobelPrizeShare
Indicates the proportion or fraction of a Nobel Prize that is allocated to a particular laureate or laureate entity.
-
C.
notableLaureatesInclude
Indicates that a group, institution, or award has among its distinguished recipients or members certain specified laureates.
-
D.
hasLaureate
Indicates that an entity (such as an award or prize) has a specific person or group as its laureate or recipient.
-
E.
authorNobelYear
Indicates the year in which an author received a Nobel Prize.
- 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_69b34539638c8190abfea3eb29425210 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b354e940d48190b49cca6796d60de4 |
completed | March 13, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69b34f5d0c54819085c08533bb58030a |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:29 p.m.