Triple
T2815292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Euler–Lagrange equation |
E54267
|
entity |
| Predicate | fieldTheoreticForm |
P42356
|
FINISHED |
| Object | ∂ℒ/∂φ − ∂_μ(∂ℒ/∂(∂_μφ)) = 0 |
—
|
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: ∂ℒ/∂φ − ∂_μ(∂ℒ/∂(∂_μφ)) = 0 | Statement: [Euler–Lagrange equation, fieldTheoreticForm, ∂ℒ/∂φ − ∂_μ(∂ℒ/∂(∂_μφ)) = 0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fieldTheoreticForm Context triple: [Euler–Lagrange equation, fieldTheoreticForm, ∂ℒ/∂φ − ∂_μ(∂ℒ/∂(∂_μφ)) = 0]
-
A.
fieldAdvanced
Indicates that a particular field or attribute has progressed beyond a basic or standard level, reflecting a more complex, specialized, or developed state.
-
B.
formerField
Indicates that an entity previously had a particular field, role, or area of activity, but no longer does.
-
C.
alternativeForm
Indicates that one entity is an alternative version, variant, or representation of another entity.
-
D.
fieldElement
Indicates that one entity is an element or member of a specified field (such as a mathematical or data field).
-
E.
mathematicallyFormulatedIn
chosen
Indicates that something is expressed, defined, or represented using mathematical formulas, equations, or formal mathematical structures within 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_69ab49de0af08190b3da69683be1e728 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde4d29488190a32461906dd9ea7e |
completed | March 7, 2026, 8:14 a.m. |
| PD | Predicate disambiguation | batch_69abdd0740208190911dc9c9546a79ae |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:59 p.m.