Triple
T1095738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Q-balls |
E24266
|
entity |
| Predicate | canDecayInto |
P5370
|
FINISHED |
| Object | standard model particles in unstable scenarios |
—
|
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: standard model particles in unstable scenarios | Statement: [Q-balls, canDecayInto, standard model particles in unstable scenarios]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canDecayInto Context triple: [Q-balls, canDecayInto, standard model particles in unstable scenarios]
-
A.
decayMode
chosen
Indicates the specific process or pathway by which an unstable entity transforms or decays into other products.
-
B.
decayWidth
Indicates the total probability per unit time (or corresponding energy measure) that an unstable particle will decay via all possible channels.
-
C.
breaksDownWhen
Indicates that one entity becomes nonfunctional, damaged, or fails when subjected to the presence, action, or conditions imposed by another entity.
-
D.
canLeadTo
Indicates that one entity, condition, or event has the potential to cause, result in, or bring about another.
-
E.
canAlsoBe
Indicates that something has an additional possible state, role, or classification beyond its primary one.
- 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b99e92308190b8a8c499e1630672 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b743175481908f3967e589717c55 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.