Triple
T5570772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fermat curve |
E146193
|
entity |
| Predicate | hasComplexPoints |
P64882
|
FINISHED |
| Object | compact Riemann surface for n ≥ 3 |
—
|
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: compact Riemann surface for n ≥ 3 | Statement: [Fermat curve, hasComplexPoints, compact Riemann surface for n ≥ 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasComplexPoints Context triple: [Fermat curve, hasComplexPoints, compact Riemann surface for n ≥ 3]
-
A.
hasComplex
Indicates that one entity possesses, is associated with, or is part of a larger composite structure or complex formed with another entity.
-
B.
hasComplexity
Indicates that something possesses a certain level or type of complexity, often in terms of structure, behavior, or difficulty.
-
C.
hasNumberOfPoints
Indicates that an entity is associated with a specific count of points it possesses or comprises.
-
D.
hasExtremePoint
Indicates that one entity possesses or includes another entity that is an extreme (e.g., maximum or minimum) point within its structure or boundary.
-
E.
hasInflectionPointsAt
Indicates that a function or curve has inflection points located at the specified positions or values.
- 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_69c008ffed108190a084602227af6157 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020502a288190af37f9ebb88fccae |
completed | March 22, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69c01b12826c8190969a584d0f53aa44 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f4032408190a4f0d2eb21ebd870 |
completed | March 22, 2026, 4:56 p.m. |
Created at: March 22, 2026, 3:37 p.m.