Triple
T18815810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | neutron |
E460130
|
entity |
| Predicate | quarkModel |
P133528
|
FINISHED |
| Object | three-quark state |
—
|
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: three-quark state | Statement: [neutron, quarkModel, three-quark state]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: quarkModel Context triple: [neutron, quarkModel, three-quark state]
-
A.
quarkModelPredictedBy
Indicates that a quark model is predicted, proposed, or derived by a particular theory, framework, or researcher.
-
B.
generationOfQuarks
Indicates the process or event in which quarks are produced or brought into existence, typically through high-energy interactions or transformations.
-
C.
hasValenceQuarks
Indicates that one entity possesses the specified quarks as its constituent valence quarks.
-
D.
hasQuarkFlavors
Indicates that an entity (such as a particle) possesses specific types (flavors) of quarks as its constituents.
-
E.
hasAntiquark
Indicates that one particle is associated with, or contains, a corresponding antiquark as part of its composition or structure.
- 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a3e092e081908fc310c70f646e79 |
completed | April 20, 2026, 3:56 a.m. |
| PD | Predicate disambiguation | batch_69e48d1b10ec8190985c6fb5766ff981 |
completed | April 19, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e49a9bcc0c81908df3e513fd6762ff |
completed | April 19, 2026, 9:04 a.m. |
Created at: April 10, 2026, 11:53 a.m.