Triple
T28758846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Polyakov–Nambu–Jona-Lasinio model |
E731749
|
entity |
| Predicate | effectiveDegreesOfFreedom |
P177133
|
FINISHED |
| Object | constituent quarks |
—
|
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: constituent quarks | Statement: [Polyakov–Nambu–Jona-Lasinio model, effectiveDegreesOfFreedom, constituent quarks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectiveDegreesOfFreedom Context triple: [Polyakov–Nambu–Jona-Lasinio model, effectiveDegreesOfFreedom, constituent quarks]
-
A.
hasDegreeOfFreedom
Indicates that one entity possesses a specific independent parameter or mode in which it can vary or move relative to another entity or within a system.
-
B.
correspondsToStudentTWithDegreesOfFreedom
Indicates that something matches or is associated with a Student’s t-distribution characterized by a specific number of degrees of freedom.
-
C.
dimensionCount
Indicates the number of distinct dimensions or axes associated with an entity or data structure.
-
D.
hasNumberOfDegrees
Indicates the quantity of academic degrees that an entity possesses.
-
E.
numberOfIndependentEquations
Indicates the count of distinct, non-redundant equations that independently constrain or relate the variables in a system.
- 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_69f043ed68a881909e858a06bab7a247 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f6f85bfba48190aba95b40642a8ca7 |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f65fd1d08190b88e5e68ba268500 |
completed | May 3, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69f6f854486c81909396d944a55e03ab |
completed | May 3, 2026, 7:25 a.m. |
Created at: April 28, 2026, 6:10 a.m.