Triple
T11098631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | (2,3,7) triangle group |
E262443
|
entity |
| Predicate | hasTriangleAngle |
P97235
|
FINISHED |
| Object | π/2 |
—
|
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: π/2 | Statement: [(2,3,7) triangle group, hasTriangleAngle, π/2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTriangleAngle Context triple: [(2,3,7) triangle group, hasTriangleAngle, π/2]
-
A.
hasTriangle
Indicates that an entity possesses, contains, or is associated with a triangle.
-
B.
satisfiesTriangleInequality
Indicates that the distances or side lengths among three points or segments obey the triangle inequality, where each length is less than or equal to the sum of the other two.
-
C.
hasTriangleColor
Indicates that a triangle-shaped element or object possesses a specific color.
-
D.
cornerOfTriangle
Indicates that the subject is a vertex (corner point) belonging to a specific triangle.
-
E.
hasNumberOfTriangles
Indicates that an entity is associated with a specific count of triangles it contains or involves.
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79a0b2890819081c4efc50e995cdd |
completed | April 9, 2026, 12:22 p.m. |
| PD | Predicate disambiguation | batch_69d7441aa3548190b92dbde57841c135 |
completed | April 9, 2026, 6:15 a.m. |
| PDg | Predicate description generation | batch_69d750ca52ec8190a559432a5de106fd |
completed | April 9, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:27 p.m.