Triple
T31797306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heisenberg–Euler effective Lagrangian |
E811631
|
entity |
| Predicate | capturesEffectOf |
P172313
|
FINISHED |
| Object | virtual electron–positron pairs |
—
|
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: virtual electron–positron pairs | Statement: [Heisenberg–Euler effective Lagrangian, capturesEffectOf, virtual electron–positron pairs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capturesEffectOf Context triple: [Heisenberg–Euler effective Lagrangian, capturesEffectOf, virtual electron–positron pairs]
-
A.
eventEffect
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
-
B.
hasEffectIn
Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
-
C.
canonicalEffect
Indicates the standard or primary effect that an action, event, or entity is typically understood to produce.
-
D.
predictedEffect
Indicates that one entity is expected to cause, influence, or result in a particular outcome or consequence for another entity.
-
E.
recognitionEffectOn
Indicates the effect or consequence that an act of recognition by one entity has on another entity or state.
- 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_69f348e70d188190b4637c5509f81274 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6ac1e180c81909b949e017345304d |
completed | May 3, 2026, 1:59 a.m. |
| PD | Predicate disambiguation | batch_69f6aa21f2508190a204a424ffc00ca6 |
completed | May 3, 2026, 1:51 a.m. |
| PDg | Predicate description generation | batch_69f6aac95c1481909fff33702d0a6c37 |
completed | May 3, 2026, 1:54 a.m. |
Created at: April 30, 2026, 11:41 p.m.