Triple
T5570710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fermat point |
E146192
|
entity |
| Predicate | angleProperty |
P64876
|
FINISHED |
| Object | forms 120-degree angles between segments to the vertices in an acute triangle |
—
|
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: forms 120-degree angles between segments to the vertices in an acute triangle | Statement: [Fermat point, angleProperty, forms 120-degree angles between segments to the vertices in an acute triangle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: angleProperty Context triple: [Fermat point, angleProperty, forms 120-degree angles between segments to the vertices in an acute triangle]
-
A.
orientationProperty
Indicates that one entity has a specific spatial or directional orientation in relation to another entity or reference frame.
-
B.
depictionAngle
Indicates the angle or viewpoint from which something is visually depicted or represented.
-
C.
angleBetweenWalls
Indicates the measure of the geometric angle formed at the intersection of two walls.
-
D.
legOrientation
Indicates the relative positioning or directional alignment of an entity’s leg(s) with respect to a reference frame or another object.
-
E.
scalingProperty
Indicates how a quantity or behavior changes in proportion to changes in another variable, typically under resizing or rescaling conditions.
- 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_69c008ffed108190a084602227af6157 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020502a288190af37f9ebb88fccae |
completed | March 22, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69c01b12826c8190969a584d0f53aa44 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f4032408190a4f0d2eb21ebd870 |
completed | March 22, 2026, 4:56 p.m. |
Created at: March 22, 2026, 3:37 p.m.