Triple
T8454740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Menger curvature |
E199891
|
entity |
| Predicate | usedToQuantify |
P4227
|
FINISHED |
| Object | how far three points deviate from being collinear |
—
|
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: how far three points deviate from being collinear | Statement: [Menger curvature, usedToQuantify, how far three points deviate from being collinear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedToQuantify Context triple: [Menger curvature, usedToQuantify, how far three points deviate from being collinear]
-
A.
usedToQuantize
Indicates that one entity serves as the quantization method, scheme, or tool applied to another entity.
-
B.
quantifies
chosen
Indicates that one entity expresses or specifies the amount, number, or degree of another entity.
-
C.
usesQuantity
Indicates that one entity employs or applies a specified amount or measure of another entity in performing an action or fulfilling a function.
-
D.
quantificationType
Indicates the specific kind or category of quantity or measurement being applied in a given context.
-
E.
quantifiesOver
Indicates that one entity expresses a quantity, measurement, or numerical specification that applies to or ranges over another entity.
- 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_69ca8318231881908fd1bc1c4d45d286 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe48ca9988190b60ebd09a135194d |
completed | March 31, 2026, 3:13 p.m. |
| PD | Predicate disambiguation | batch_69cbd0fc634481909842c0a30077bfde |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:10 p.m.