Triple
T26255210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poincaré upper half-plane model |
E656696
|
entity |
| Predicate | hasVolumeElement |
P165340
|
FINISHED |
| Object | dA = dx dy / y² |
—
|
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: dA = dx dy / y² | Statement: [Poincaré upper half-plane model, hasVolumeElement, dA = dx dy / y²]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVolumeElement Context triple: [Poincaré upper half-plane model, hasVolumeElement, dA = dx dy / y²]
-
A.
hasExposedVolume
Indicates that a volume or space is open or exposed to its surroundings rather than fully enclosed or covered.
-
B.
hasThreeVolumeStructureRole
Indicates that an entity participates in or fulfills a role within a three-volume structural organization or framework.
-
C.
hasVolumeDescriptor
Indicates that something is associated with a qualitative or quantitative description of its volume.
-
D.
hasVolumeContrasts
Indicates that an entity exhibits notable differences in loudness or intensity across its parts or over time.
-
E.
hasLargeVolume
Indicates that an entity possesses or is characterized by a comparatively large physical or quantitative volume.
- 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_69ee5b4d25ac819086acb51184602576 |
completed | April 26, 2026, 6:37 p.m. |
| NER | Named-entity recognition | batch_69f658a91ba0819084fbe3dd8a09f7cd |
completed | May 2, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f657f2c8b08190bfeb3173ef78207d |
completed | May 2, 2026, 8 p.m. |
Created at: April 26, 2026, 9:08 p.m.