Triple
T7833349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyapunov inequality |
E181627
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | Lyapunov exponent |
E181623
|
NE 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: Lyapunov exponent | Statement: [Lyapunov inequality, relatedTo, Lyapunov exponent]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lyapunov exponent Context triple: [Lyapunov inequality, relatedTo, Lyapunov exponent]
-
A.
Lyapunov exponents
chosen
Lyapunov exponents are quantitative measures in dynamical systems theory that characterize the rates at which nearby trajectories diverge or converge, indicating the presence and strength of chaos.
-
B.
Lyapunov dimension
The Lyapunov dimension is a fractal dimension used in dynamical systems theory to quantify the effective number of degrees of freedom of a chaotic attractor based on its Lyapunov exponents.
-
C.
Lyapunov vector
A Lyapunov vector is a mathematical construct in dynamical systems theory that characterizes the directions in phase space associated with exponential growth or decay rates quantified by Lyapunov exponents.
-
D.
Kolmogorov–Sinai entropy
Kolmogorov–Sinai entropy is a fundamental invariant in dynamical systems theory that quantifies the average rate of information production or unpredictability of a measure-preserving transformation.
-
E.
Lyapunov time
Lyapunov time is a measure in dynamical systems theory that quantifies how long it takes for small differences in initial conditions to grow exponentially and significantly affect a system’s future behavior, indicating the timescale of predictability.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca8284a25c8190a1a20afad30da792 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb064a47648190af2ca2b336584a92 |
completed | March 30, 2026, 11:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd66ecea6c819097a74513c5d84193 |
completed | April 1, 2026, 6:41 p.m. |
Created at: March 30, 2026, 4:45 p.m.