Triple
T9637438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Born–Infeld electrodynamics |
E232968
|
entity |
| Predicate | typeOfNonlinearity |
P89388
|
FINISHED |
| Object | square-root Lagrangian nonlinearity |
—
|
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: square-root Lagrangian nonlinearity | Statement: [Born–Infeld electrodynamics, typeOfNonlinearity, square-root Lagrangian nonlinearity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfNonlinearity Context triple: [Born–Infeld electrodynamics, typeOfNonlinearity, square-root Lagrangian nonlinearity]
-
A.
linearity
Indicates that a relationship between quantities preserves addition and scalar multiplication, so outputs change in direct proportion to inputs.
-
B.
activationFunction
Indicates the specific mathematical transformation applied to a neuron's input to produce its output in a computational or neural model.
-
C.
kernelType
Indicates the specific kind or category of kernel associated with or used by an entity.
-
D.
derivativesType
Indicates the specific kind or category of derivative relationship that exists between two related entities.
-
E.
valueFunctionShape
Indicates the mathematical form or structural pattern of a value function used to evaluate states, actions, or outcomes in a decision or optimization process.
- 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_69ca848940cc8190b97cec654cb3bb4a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b5045cc8190ab717f42d803e010 |
completed | April 1, 2026, 10:25 p.m. |
| PD | Predicate disambiguation | batch_69ccd5acfa5c8190aaba3cf548723604 |
completed | April 1, 2026, 8:22 a.m. |
| PDg | Predicate description generation | batch_69ccd93fc45c8190a823305e461e581d |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:11 p.m.