Triple
T31703484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | q-Gaussian distribution |
E809119
|
entity |
| Predicate | isNonNormalizableFor |
P172444
|
FINISHED |
| Object | q ≥ 3 |
—
|
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: q ≥ 3 | Statement: [q-Gaussian distribution, isNonNormalizableFor, q ≥ 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNonNormalizableFor Context triple: [q-Gaussian distribution, isNonNormalizableFor, q ≥ 3]
-
A.
usesNormalization
Indicates that one entity applies or relies on a normalization process or technique in relation to another entity or data.
-
B.
isNormalIn
Indicates that one group is a normal subgroup of another group, meaning it is invariant under conjugation by elements of the larger group.
-
C.
isRenormalizable
Indicates that a physical theory or interaction can have its infinities systematically absorbed into a finite number of redefined parameters, yielding well-defined, predictive results at all relevant scales.
-
D.
haveNormalization
Indicates that one entity serves as a normalization or standardized form of another entity.
-
E.
hasNonStandardForm
Indicates that an entity possesses a form, variant, or representation that deviates from the standard, canonical, or commonly accepted form.
- 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_69f348de914081909fc8edff56f34dbe |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6abe15d5c81909ccf4ce37f78bc43 |
completed | May 3, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69f6aa20a1588190a53533fc9764efb2 |
completed | May 3, 2026, 1:51 a.m. |
| PDg | Predicate description generation | batch_69f6aaf31a548190b2f792ff4b8c002a |
completed | May 3, 2026, 1:54 a.m. |
Created at: April 30, 2026, 11:13 p.m.