Triple
T4414020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salam–Weinberg model |
E94919
|
entity |
| Predicate | unifies |
P35330
|
FINISHED |
| Object | electromagnetic interaction |
—
|
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: electromagnetic interaction | Statement: [Salam–Weinberg model, unifies, electromagnetic interaction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: unifies Context triple: [Salam–Weinberg model, unifies, electromagnetic interaction]
-
A.
unites
chosen
Indicates that one entity brings together multiple entities into a single, cohesive whole or shared state.
-
B.
uniformizedBy
Indicates that one entity has been made uniform, standardized, or brought into a consistent form or structure by another entity.
-
C.
wasUnifiedWith
Indicates that two or more previously separate entities were brought together to form a single unified whole.
-
D.
union
Indicates that two or more sets are combined into a single set containing all elements that belong to at least one of them.
-
E.
unificationPossible
Indicates that two entities can be combined or reconciled into a single, consistent representation under a shared set of constraints or rules.
- 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.