Triple
T38260684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abreu equation |
E1017919
|
entity |
| Predicate | hasDifferentialOrder |
P200936
|
FINISHED |
| Object | four |
—
|
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: four | Statement: [Abreu equation, hasDifferentialOrder, four]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDifferentialOrder Context triple: [Abreu equation, hasDifferentialOrder, four]
-
A.
hasDifferentials
Indicates that one entity possesses or is associated with differential components, mechanisms, or calculations relative to another entity.
-
B.
hasDifferentialForm
Indicates that one entity is associated with, or can be represented by, a specific differential form in a mathematical or geometric context.
-
C.
isDifferential
Indicates that one quantity represents the infinitesimal change or derivative of another with respect to a given variable.
-
D.
hasDifferential
Indicates that one entity is the derivative or rate-of-change expression corresponding to another entity.
-
E.
hasDerivativeTerm
Indicates that one term is derived or obtained from another term, typically through a transformation, calculation, or logical inference.
- 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_69f76de33e4481909099fa812709bd42 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ffb97b8ff8819088b105d99a0820c9 |
completed | May 9, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69ffb88ef7388190a710120ed76edc0e |
completed | May 9, 2026, 10:43 p.m. |
| PDg | Predicate description generation | batch_69ffb97ae1508190bf3addd6e2aac281 |
completed | May 9, 2026, 10:47 p.m. |
Created at: May 3, 2026, 4:30 p.m.