Triple
T14438406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L-function |
E358024
|
entity |
| Predicate | oftenNormalizedTo |
P114275
|
FINISHED |
| Object | satisfy symmetric functional equation |
—
|
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: satisfy symmetric functional equation | Statement: [L-function, oftenNormalizedTo, satisfy symmetric functional equation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenNormalizedTo Context triple: [L-function, oftenNormalizedTo, satisfy symmetric functional equation]
-
A.
normalizationAttempt
Indicates an effort to convert something into a standard or consistent form according to defined rules or criteria.
-
B.
uniformizes
Indicates making multiple entities or elements consistent, standardized, or uniform in form, appearance, or behavior.
-
C.
uniformizedBy
Indicates that one entity has been made uniform, standardized, or brought into a consistent form or structure by another entity.
-
D.
normIs
Indicates that something conforms to, or is characterized by, a particular standard, rule, or norm.
-
E.
usesNormalization
Indicates that one entity applies or relies on a normalization process or technique in relation to another entity or data.
- 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de914a45ec81909ab8ccf302047d7f |
completed | April 14, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69de5c3a02fc819097373f97a260cdeb |
completed | April 14, 2026, 3:24 p.m. |
| PDg | Predicate description generation | batch_69de5fb4de14819092acdecbd201d672 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:18 a.m.