Triple
T25550027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mordell curve |
E640411
|
entity |
| Predicate | hasIntegralPoints |
P174323
|
FINISHED |
| Object | finite set for fixed nonzero k over ℤ |
—
|
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: finite set for fixed nonzero k over ℤ | Statement: [Mordell curve, hasIntegralPoints, finite set for fixed nonzero k over ℤ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIntegralPoints Context triple: [Mordell curve, hasIntegralPoints, finite set for fixed nonzero k over ℤ]
-
A.
hasLinesThroughEachPoint
Indicates that for every point in the relevant space or set, there exists at least one line that passes through that point.
-
B.
hasNumberOfPoints
Indicates that an entity is associated with a specific count of points it possesses or comprises.
-
C.
hasIntegralForm
Indicates that one entity is the integral (antiderivative) form or representation of another entity.
-
D.
hasRightAngleIntersections
Indicates that the entities intersect each other at right (90-degree) angles.
-
E.
hasIntegralRepresentation
Indicates that one entity can be expressed or represented as an integral involving the other entity.
- 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_69e75dc101a881909fd33b02174e9768 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f6c20f209081909fb9ac8f95069f04 |
completed | May 3, 2026, 3:33 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
| PDg | Predicate description generation | batch_69f6c125695c81909704c67bef4ce5b2 |
completed | May 3, 2026, 3:29 a.m. |
Created at: April 21, 2026, 3:36 p.m.