Triple
T6833699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cramér–Rao bound |
E157397
|
entity |
| Predicate | usesConcept |
P531
|
FINISHED |
| Object | Fisher information matrix |
E212219
|
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: Fisher information matrix | Statement: [Cramér–Rao bound, usesConcept, Fisher information matrix]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fisher information matrix Context triple: [Cramér–Rao bound, usesConcept, Fisher information matrix]
-
A.
Fisher information
chosen
Fisher information is a fundamental concept in statistics that quantifies how much information an observable random variable carries about an unknown parameter, playing a key role in estimation theory and the Cramér–Rao bound.
-
B.
Cramér–Rao bound
The Cramér–Rao bound is a fundamental result in statistical estimation theory that gives a lower limit on the variance of any unbiased estimator of a parameter, characterizing the best possible precision achievable.
-
C.
Chernoff information
Chernoff information is a measure in information theory and statistics that quantifies the exponential rate at which the error probability decays when optimally distinguishing between two probability distributions.
-
D.
Bhattacharyya distance
Bhattacharyya distance is a statistical measure of similarity between two probability distributions, often used in pattern recognition and classification to quantify their overlap.
-
E.
Jacobi matrix
A Jacobi matrix is a tridiagonal matrix, often symmetric, that arises in numerical analysis and mathematical physics, particularly in the study of orthogonal polynomials and eigenvalue problems.
- 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_69c6882c53608190b99aebef079b23bd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d67936288190829fedc3729aadd8 |
completed | March 27, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c72fab60708190825876e5715c0cc4 |
completed | March 28, 2026, 1:32 a.m. |
Created at: March 27, 2026, 2:18 p.m.