Triple
T14438407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L-function |
E358024
|
entity |
| Predicate | hasCriticalStrip |
P114276
|
FINISHED |
| Object | 0 < Re(s) < 1 |
—
|
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: 0 < Re(s) < 1 | Statement: [L-function, hasCriticalStrip, 0 < Re(s) < 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCriticalStrip Context triple: [L-function, hasCriticalStrip, 0 < Re(s) < 1]
-
A.
hasCriticalView
Indicates that one entity holds a negative, skeptical, or evaluative stance toward another entity, often highlighting flaws, problems, or points of disagreement.
-
B.
hasCriticalDescriptor
Indicates that an entity is associated with a descriptor that marks it as critical, essential, or of high importance or severity.
-
C.
canBeStrippedFor
Indicates that one entity is capable of having parts or layers removed in order to benefit, prepare, or expose another entity.
-
D.
hasCommercialStrip
Indicates that an area or entity contains or is associated with a zone characterized by a concentration of commercial businesses or retail establishments.
-
E.
canBeStripped
Indicates that one entity is capable of having an outer layer, covering, or component removed from it.
- 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.