Triple

T1691916
Position Surface form Disambiguated ID Type / Status
Subject Rudolf E. Kálmán E36567 entity
Predicate knownFor P22 FINISHED
Object Kalman filter
The Kalman filter is a mathematical algorithm used to estimate the changing state of a system from noisy measurements, widely applied in control systems, navigation, and signal processing.
 E191951 NE FINISHED

How this triple was built (4 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: Kalman filter | Statement: [Rudolf E. Kálmán, knownFor, Kalman filter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kalman filter
Context triple: [Rudolf E. Kálmán, knownFor, Kalman filter]
  • A. Wiener filter
    The Wiener filter is a signal processing technique that optimally estimates a desired signal from noisy observations by minimizing the mean square error, based on statistical properties of signal and noise.
  • B. Kailath factorization in linear systems
    Kailath factorization in linear systems is a matrix factorization technique used in control and signal processing to efficiently analyze and solve linear dynamical systems.
  • C. Linear Estimation
    Linear Estimation is a foundational text in signal processing and control theory that systematically develops the theory and applications of optimal estimation, including Kalman filtering and related methods.
  • D. Innovations approach to detection and estimation
    "Innovations approach to detection and estimation" is a seminal work by Thomas Kailath that develops a powerful stochastic framework for solving signal detection and parameter estimation problems, particularly in control and communication systems.
  • E. Lyapunov equation
    The Lyapunov equation is a fundamental matrix equation in control theory and dynamical systems used to analyze the stability of equilibrium points and design stable controllers.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kalman filter
Triple: [Rudolf E. Kálmán, knownFor, Kalman filter]
Generated description
The Kalman filter is a mathematical algorithm used to estimate the changing state of a system from noisy measurements, widely applied in control systems, navigation, and signal processing.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kalman filter
Target entity description: The Kalman filter is a mathematical algorithm used to estimate the changing state of a system from noisy measurements, widely applied in control systems, navigation, and signal processing.
  • A. Wiener filter
    The Wiener filter is a signal processing technique that optimally estimates a desired signal from noisy observations by minimizing the mean square error, based on statistical properties of signal and noise.
  • B. Kailath factorization in linear systems
    Kailath factorization in linear systems is a matrix factorization technique used in control and signal processing to efficiently analyze and solve linear dynamical systems.
  • C. Linear Estimation
    Linear Estimation is a foundational text in signal processing and control theory that systematically develops the theory and applications of optimal estimation, including Kalman filtering and related methods.
  • D. Innovations approach to detection and estimation
    "Innovations approach to detection and estimation" is a seminal work by Thomas Kailath that develops a powerful stochastic framework for solving signal detection and parameter estimation problems, particularly in control and communication systems.
  • E. Lyapunov equation
    The Lyapunov equation is a fundamental matrix equation in control theory and dynamical systems used to analyze the stability of equilibrium points and design stable controllers.
  • F. None of above. chosen

Provenance (5 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_69a886151508819084fa7f1ce6e05577 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa62b097488190907e3bce234e3c77 completed March 6, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad7996a39481909152a6a799659c93 completed March 8, 2026, 1:28 p.m.
NEDg Description generation batch_69ad7bd602e4819093768853da8f506c completed March 8, 2026, 1:38 p.m.
NED2 Entity disambiguation (via description) batch_69ad8200103c81908e0b3d134b291409 completed March 8, 2026, 2:04 p.m.
Created at: March 4, 2026, 7:29 p.m.