Triple
T6833488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernoulli lemniscate |
E157392
|
entity |
| Predicate | intersectsXAxisAt |
P72979
|
FINISHED |
| Object | (±a/√2,0) |
—
|
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: (±a/√2,0) | Statement: [Bernoulli lemniscate, intersectsXAxisAt, (±a/√2,0)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intersectsXAxisAt Context triple: [Bernoulli lemniscate, intersectsXAxisAt, (±a/√2,0)]
-
A.
hasCrossingPoint
Indicates that two or more entities intersect or share at least one common point in space or along their paths.
-
B.
crossesQuadrantBoundaryAt
Indicates that an entity’s path or position passes from one quadrant into another specifically at a given point or time.
-
C.
hasEquatorCrossing
Indicates that the path or orbit of an entity crosses the equator of a reference body.
-
D.
hadCrossingPoints
Indicates that two entities intersected or overlapped at one or more specific points in space or time.
-
E.
isAxisBetween
Indicates that one entity serves as a central or reference axis positioned between two other entities in a spatial or structural arrangement.
- 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_69c6882c53608190b99aebef079b23bd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d62b1e8c8190a81d91191a54b073 |
completed | March 27, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69c6d09d95f0819091ca7f897dc21efe |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d11fab808190b18160ff3829fcc6 |
completed | March 27, 2026, 6:49 p.m. |
Created at: March 27, 2026, 2:18 p.m.