Triple
T7419991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cauchy–Kovalevskaya theorem |
E171220
|
entity |
| Predicate | initialDataGivenOn |
P76848
|
FINISHED |
| Object | non-characteristic hypersurface |
—
|
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: non-characteristic hypersurface | Statement: [Cauchy–Kovalevskaya theorem, initialDataGivenOn, non-characteristic hypersurface]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: initialDataGivenOn Context triple: [Cauchy–Kovalevskaya theorem, initialDataGivenOn, non-characteristic hypersurface]
-
A.
initialedOn
Indicates that an entity has placed its initials on or approved something on a specific date or at a specific time.
-
B.
initialOpening
Indicates the first or earliest instance in which something is opened, begun, or made accessible.
-
C.
initialReception
Indicates the nature or quality of the first response or reaction something receives when it is introduced or presented.
-
D.
initialAttitude
Indicates the starting stance, feeling, or disposition one entity holds toward another or toward a situation before any interaction or change occurs.
-
E.
initialGoal
Indicates that something represents the first or starting objective or target in a sequence of goals.
- 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_69c68a625d048190af70eb8b63bec5a0 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2ea61248190886e8e55b42ba5f1 |
completed | March 27, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c6f0345040819094c5756dfa487faf |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f1c3307481909a7f6bb69d4fddac |
completed | March 27, 2026, 9:08 p.m. |
Created at: March 27, 2026, 3:11 p.m.