Triple
T1382372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | construction of the regular 17-gon with straightedge and compass |
E29366
|
entity |
| Predicate | hasPolygonType |
P16808
|
FINISHED |
| Object | regular 17-gon |
—
|
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: regular 17-gon | Statement: [construction of the regular 17-gon with straightedge and compass, hasPolygonType, regular 17-gon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPolygonType Context triple: [construction of the regular 17-gon with straightedge and compass, hasPolygonType, regular 17-gon]
-
A.
hasHullType
Indicates that an entity possesses or is characterized by a specific type or form of hull.
-
B.
hasGeometry
Indicates that an entity is associated with a specific geometric representation or spatial form.
-
C.
hasBoundaryType
Indicates that one entity has a boundary characterized by a specific type or classification in relation to another entity or context.
-
D.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
E.
haveType
chosen
Indicates that an entity belongs to or is classified under a specified type or category.
- F. None of above.
Provenance (3 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c3361bf08190b3f6bbf82e17685b |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4befe343c81909f758440a531b5be |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.