Triple
T8144027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kepler–Poinsot polyhedra |
E190163
|
entity |
| Predicate | areRegularIn |
P80939
|
FINISHED |
| Object | Schläfli’s sense of regularity |
—
|
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: Schläfli’s sense of regularity | Statement: [Kepler–Poinsot polyhedra, areRegularIn, Schläfli’s sense of regularity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areRegularIn Context triple: [Kepler–Poinsot polyhedra, areRegularIn, Schläfli’s sense of regularity]
-
A.
isRegularAt
Indicates that a function or mapping behaves regularly (e.g., is analytic, smooth, or non-singular) at a specified point or region, without irregularities or singularities there.
-
B.
hasRegularity
Indicates that one entity exhibits a consistent, recurring pattern or uniform behavior with respect to another entity or over time.
-
C.
areOfficialIn
Indicates that an entity holds an official role, position, or capacity within another entity (such as an organization, institution, or jurisdiction).
-
D.
regulatesIn
Indicates that one entity controls, modulates, or influences the activity, expression, or behavior of another entity within a system or process.
-
E.
meetsRegularly
Indicates that two or more entities come together on a recurring or scheduled basis.
- 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_69ca82bd9900819099477cdc2eb4244f |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4444bb248190beaaa2ce4b8f3eaa |
completed | March 31, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69cb369c0d0481908762c488d7f77e74 |
completed | March 31, 2026, 2:51 a.m. |
| PDg | Predicate description generation | batch_69cb39d20e78819092ea9e04357be008 |
completed | March 31, 2026, 3:04 a.m. |
Created at: March 30, 2026, 5:36 p.m.