Triple
T26970968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexander–Spanier cohomology |
E679316
|
entity |
| Predicate | degreeNComponent |
P162496
|
FINISHED |
| Object | group of functions on (n+1)-tuples of points |
—
|
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: group of functions on (n+1)-tuples of points | Statement: [Alexander–Spanier cohomology, degreeNComponent, group of functions on (n+1)-tuples of points]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: degreeNComponent Context triple: [Alexander–Spanier cohomology, degreeNComponent, group of functions on (n+1)-tuples of points]
-
A.
degreeNumber
Indicates the specific numeric value assigned to a degree, such as its level, rank, or sequence number.
-
B.
degreeInX
Indicates that an entity holds an academic degree in a specified field or discipline.
-
C.
degreeForm
Indicates that one entity is the specific academic degree or qualification conferred in the context of another entity (such as a program, award, or credential).
-
D.
degreeOver
Indicates that one entity’s degree, level, or extent exceeds that of another entity.
-
E.
degreeIn2
Indicates that the second entity holds an academic degree in the field or program represented by the first 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_69eeeb507a7081909d516e1fa08b7d29 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f62b9e5ba88190a3c0d46edec7afe7 |
completed | May 2, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69f623a91b9c8190b2e2fdbc55cb89b6 |
completed | May 2, 2026, 4:17 p.m. |
| PDg | Predicate description generation | batch_69f625402d808190be8279d895d2b27f |
completed | May 2, 2026, 4:24 p.m. |
Created at: April 27, 2026, 6:39 a.m.