Triple
T32789660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Galois extension |
E838591
|
entity |
| Predicate | hasDegreeEqualTo |
P197935
|
FINISHED |
| Object | order of the Galois group for finite extensions |
—
|
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: order of the Galois group for finite extensions | Statement: [Galois extension, hasDegreeEqualTo, order of the Galois group for finite extensions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDegreeEqualTo Context triple: [Galois extension, hasDegreeEqualTo, order of the Galois group for finite extensions]
-
A.
hasDegree
Indicates that an entity possesses or has been awarded a specific academic or professional degree.
-
B.
hasDegreeIn
Indicates that an entity possesses an academic degree in a specified field or discipline.
-
C.
haveDegree
Indicates that an entity possesses or has obtained a specific academic or professional degree.
-
D.
hasNumberOfDegrees
Indicates the quantity of academic degrees that an entity possesses.
-
E.
hasDegreeLength
Indicates that something possesses a length measured in degrees, typically expressing angular extent or size.
- 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_69f3493b83f48190be335cd42465cecf |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69feba0f09508190b3e871c62b19ec7f |
completed | May 9, 2026, 4:37 a.m. |
| PD | Predicate disambiguation | batch_69feb957fe7c8190969fb31a6d1a59c8 |
completed | May 9, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69feba0e362c81909883a3f24a4a9545 |
completed | May 9, 2026, 4:37 a.m. |
Created at: May 1, 2026, 1:14 a.m.