Triple
T33985401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siegel modular form |
E871397
|
entity |
| Predicate | degree1SpecialCase |
P7025
|
FINISHED |
| Object | elliptic modular form |
—
|
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: elliptic modular form | Statement: [Siegel modular form, degree1SpecialCase, elliptic modular form]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: degree1SpecialCase Context triple: [Siegel modular form, degree1SpecialCase, elliptic modular form]
-
A.
specialCaseOf
chosen
Indicates that one entity represents a more specific, exceptional, or restricted instance of the general situation, rule, or relationship expressed by another entity.
-
B.
degreeOnePart
Indicates that one entity is a component or part of another entity to exactly one degree or level in a part-whole hierarchy.
-
C.
degreeNumber
Indicates the specific numeric value assigned to a degree, such as its level, rank, or sequence number.
-
D.
degreeExample
Indicates that an entity serves as an illustrative example or instance of a particular degree, level, or extent of something.
-
E.
degreeOver
Indicates that one entity’s degree, level, or extent exceeds that 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_69f3499e964c8190b674b03f6f791b4b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70fb4f18c819099ef6d9177b7d205 |
completed | May 3, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f70f3a54d481909ba6bdda3647b761 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:50 a.m.