Triple

T10152162
Position Surface form Disambiguated ID Type / Status
Subject Graham C. Goodwin E232670 entity
Predicate notableWork P4 FINISHED
Object Dynamic System Identification: Experiment Design and Data Analysis
"Dynamic System Identification: Experiment Design and Data Analysis" is a technical book that presents methods for designing experiments and analyzing data to model and identify dynamic systems in engineering and control applications.
E843468 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: Dynamic System Identification: Experiment Design and Data Analysis | Statement: [Graham C. Goodwin, notableWork, Dynamic System Identification: Experiment Design and Data Analysis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dynamic System Identification: Experiment Design and Data Analysis
Context triple: [Graham C. Goodwin, notableWork, Dynamic System Identification: Experiment Design and Data Analysis]
  • A. Feedback Systems: An Introduction for Scientists and Engineers
    Feedback Systems: An Introduction for Scientists and Engineers is a widely used textbook that provides a modern, rigorous introduction to control theory and feedback principles for science and engineering students.
  • B. Prediction and Regulation by Linear Least-Square Methods
    "Prediction and Regulation by Linear Least-Square Methods" is a foundational monograph in stochastic control and time-series analysis that systematically develops linear least-squares techniques for prediction, filtering, and optimal regulation.
  • C. Åström–Wittenmark adaptive control framework
    The Åström–Wittenmark adaptive control framework is a foundational methodology in control theory that systematically designs controllers capable of adjusting their parameters in real time to handle unknown or time-varying system dynamics.
  • D. Quantitative Feedback Theory
    Quantitative Feedback Theory is a robust control design methodology that uses frequency-domain techniques and quantitative bounds to ensure system performance and stability under uncertainty.
  • E. Sampled-Data Control Systems
    Sampled-Data Control Systems is a foundational work in control theory that systematically develops the analysis and design of systems combining continuous-time dynamics with discrete-time sampling.
  • 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: Dynamic System Identification: Experiment Design and Data Analysis
Triple: [Graham C. Goodwin, notableWork, Dynamic System Identification: Experiment Design and Data Analysis]
Generated description
"Dynamic System Identification: Experiment Design and Data Analysis" is a technical book that presents methods for designing experiments and analyzing data to model and identify dynamic systems in engineering and control applications.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dynamic System Identification: Experiment Design and Data Analysis
Target entity description: "Dynamic System Identification: Experiment Design and Data Analysis" is a technical book that presents methods for designing experiments and analyzing data to model and identify dynamic systems in engineering and control applications.
  • A. Feedback Systems: An Introduction for Scientists and Engineers
    Feedback Systems: An Introduction for Scientists and Engineers is a widely used textbook that provides a modern, rigorous introduction to control theory and feedback principles for science and engineering students.
  • B. Prediction and Regulation by Linear Least-Square Methods
    "Prediction and Regulation by Linear Least-Square Methods" is a foundational monograph in stochastic control and time-series analysis that systematically develops linear least-squares techniques for prediction, filtering, and optimal regulation.
  • C. Åström–Wittenmark adaptive control framework
    The Åström–Wittenmark adaptive control framework is a foundational methodology in control theory that systematically designs controllers capable of adjusting their parameters in real time to handle unknown or time-varying system dynamics.
  • D. Quantitative Feedback Theory
    Quantitative Feedback Theory is a robust control design methodology that uses frequency-domain techniques and quantitative bounds to ensure system performance and stability under uncertainty.
  • E. Sampled-Data Control Systems
    Sampled-Data Control Systems is a foundational work in control theory that systematically develops the analysis and design of systems combining continuous-time dynamics with discrete-time sampling.
  • 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_69ca84885e48819088a31b127cf44904 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cdec361c7c8190b8fd841d728d5bbe completed April 2, 2026, 4:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e64b5a40819093f29ec34cb0a763 completed April 5, 2026, 10:46 p.m.
NEDg Description generation batch_69d2e7408e58819083c43e334a87a09f completed April 5, 2026, 10:50 p.m.
NED2 Entity disambiguation (via description) batch_69d2e7b854d08190ac2af642970b7f09 completed April 5, 2026, 10:52 p.m.
Created at: March 30, 2026, 9:08 p.m.