Triple
T3576650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bethe–Weizsäcker cycle |
E75704
|
entity |
| Predicate | netEffect |
P1634
|
FINISHED |
| Object | four protons fused into one helium-4 nucleus |
—
|
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: four protons fused into one helium-4 nucleus | Statement: [Bethe–Weizsäcker cycle, netEffect, four protons fused into one helium-4 nucleus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: netEffect Context triple: [Bethe–Weizsäcker cycle, netEffect, four protons fused into one helium-4 nucleus]
-
A.
notableEffect
Indicates that one entity has a significant impact, consequence, or influence on another entity or situation.
-
B.
effectOnSystem
Indicates the influence, change, or impact that one entity, action, or condition has on the state or behavior of a system.
-
C.
sideEffect
Indicates that one entity is an unintended or secondary effect resulting from the use or occurrence of another entity.
-
D.
primaryEffect
chosen
Indicates the main direct outcome or consequence that results from a given cause, action, or condition.
-
E.
tookEffect
Indicates that a change, rule, condition, or event became active, operative, or started producing its intended consequences.
- 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_69ad85d5e3008190bdfe0bacdd1f5a1b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0dba238819083a1d09005c312b8 |
completed | March 8, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69adb83810c481909c645c08b978edc1 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:21 p.m.