Triple
T6780948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lagrangian mechanics |
E155679
|
entity |
| Predicate | coreQuantity |
P9758
|
FINISHED |
| Object | kinetic energy |
—
|
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: kinetic energy | Statement: [Lagrangian mechanics, coreQuantity, kinetic energy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coreQuantity Context triple: [Lagrangian mechanics, coreQuantity, kinetic energy]
-
A.
usesQuantity
Indicates that one entity employs or applies a specified amount or measure of another entity in performing an action or fulfilling a function.
-
B.
quantityType
chosen
Indicates that one entity is the type or category of quantity to which another entity (a specific measured or measurable amount) belongs.
-
C.
quantifies
Indicates that one entity expresses or specifies the amount, number, or degree of another entity.
-
D.
numberOfUnits
Indicates the quantity or count of discrete units associated with an entity or relationship.
-
E.
quantificationType
Indicates the specific kind or category of quantity or measurement being applied in a given context.
- 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_69c688162bf8819088b664b5c3b5be7a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d26b32c0819093f86b1002260660 |
completed | March 27, 2026, 6:54 p.m. |
| PD | Predicate disambiguation | batch_69c6d095dcac8190bb9b943f50a7f885 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:14 p.m.