Triple
T32789991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gröbner fan |
E838598
|
entity |
| Predicate | coneRepresents |
P175119
|
FINISHED |
| Object | set of weight vectors with same initial ideal |
—
|
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: set of weight vectors with same initial ideal | Statement: [Gröbner fan, coneRepresents, set of weight vectors with same initial ideal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coneRepresents Context triple: [Gröbner fan, coneRepresents, set of weight vectors with same initial ideal]
-
A.
cornerRepresents
Indicates that a particular corner in a structure, diagram, or space stands for or symbolizes another element, concept, or feature.
-
B.
componentRepresents
Indicates that one component stands in for, symbolizes, or models another entity or concept within a system or context.
-
C.
poleRepresentation
Indicates a representation of something in terms of its poles, typically expressing a system, function, or object using its pole-based form.
-
D.
coneType
Indicates the specific category or style of cone associated with an entity (e.g., type, shape, or design of the cone).
-
E.
boundaryRepresents
Indicates that a boundary serves as a representation or delineation of another spatial, conceptual, or administrative extent.
- 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_69f3493b83f48190be335cd42465cecf |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6cee547108190ad3bc84297d8f516 |
completed | May 3, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1667a48190b42684f6ec22dae9 |
completed | May 3, 2026, 4:16 a.m. |
| PDg | Predicate description generation | batch_69f6ce6c76bc8190b865343d3f5810c9 |
completed | May 3, 2026, 4:26 a.m. |
Created at: May 1, 2026, 1:14 a.m.