Triple
T209645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Newtonian mechanics |
E4685
|
entity |
| Predicate | formalism |
P6279
|
FINISHED |
| Object | Lagrangian mechanics |
—
|
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: Lagrangian mechanics | Statement: [Newtonian mechanics, formalism, Lagrangian mechanics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formalism Context triple: [Newtonian mechanics, formalism, Lagrangian mechanics]
-
A.
formalityLevel
Indicates the degree of social or stylistic formality characterizing an interaction, expression, or context between entities.
-
B.
logicalForm
Indicates a relationship where an expression is associated with its structured, formal logical representation.
-
C.
termFormalizedBy
chosen
Indicates that a given term has been formally defined, specified, or codified by a particular formalization (such as a formal theory, document, or system).
-
D.
formed
Indicates that one entity came into existence, shape, or organization as a result of the actions or processes involving another entity.
-
E.
format
Indicates the specific arrangement, structure, or presentation style in which something is organized or expressed.
- 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_69a25737567c81908f9c505300239181 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25e8b9b908190b69a3f0594b95f7e |
completed | Feb. 28, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69a25b4e3c2881908d83e8218aa9f2d9 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:51 a.m.