Triple
T1483872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Conway polynomial |
E29419
|
entity |
| Predicate | degreeProperty |
P3633
|
FINISHED |
| Object | degree of ∇(K) is bounded above by twice the genus of K |
—
|
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: degree of ∇(K) is bounded above by twice the genus of K | Statement: [Conway polynomial, degreeProperty, degree of ∇(K) is bounded above by twice the genus of K]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: degreeProperty Context triple: [Conway polynomial, degreeProperty, degree of ∇(K) is bounded above by twice the genus of K]
-
A.
isDegreeOf
Indicates that one entity is an academic or professional degree held, pursued, or associated with another entity.
-
B.
hasDegree
Indicates that an entity possesses or has been awarded a specific academic or professional degree.
-
C.
typicalDegree
Indicates the usual or characteristic level, intensity, or extent to which something holds or applies in a given context.
-
D.
depthRank
Indicates the relative ordering of entities based on how deep or distant they are along a specified depth dimension or hierarchy.
-
E.
dimension
chosen
Indicates that one entity specifies a measurable extent or size attribute (such as length, width, height, or similar quantitative property) of another entity.
- F. None of above.
Provenance (3 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_69a498da82e08190ba833330d05f380f |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c679714c8190ac53630fb49e19c5 |
completed | March 1, 2026, 11:06 p.m. |
| PD | Predicate disambiguation | batch_69a4c486eacc81909c272f9bdf50a7c3 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:12 p.m.