Triple

T12063466
Position Surface form Disambiguated ID Type / Status
Subject Andrew Viterbi E287233 entity
Predicate familyName P18 FINISHED
Object Viterbi
Viterbi is a surname most prominently associated with Andrew Viterbi, the Italian-American engineer and co-inventor of the Viterbi algorithm used in digital communications and error correction.
 E962817 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: Viterbi | Statement: [Andrew Viterbi, familyName, Viterbi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Viterbi
Context triple: [Andrew Viterbi, familyName, Viterbi]
  • A. Viterbi algorithm
    The Viterbi algorithm is a dynamic programming method used to find the most likely sequence of hidden states in probabilistic models such as Hidden Markov Models, widely applied in fields like digital communications, speech recognition, and bioinformatics.
  • B. Baum–Welch algorithm
    The Baum–Welch algorithm is an expectation-maximization method used to train the parameters of hidden Markov models from observed data.
  • C. forward-backward algorithm
    The forward-backward algorithm is a dynamic programming method for computing posterior state probabilities in hidden Markov models, widely used in tasks like sequence labeling and speech recognition.
  • D. Hidden Markov Model
    A Hidden Markov Model is a statistical model that represents systems with unobserved (hidden) states generating observable outputs, widely used for sequence analysis tasks such as speech recognition, bioinformatics, and natural language processing.
  • E. Bellman
    Bellman is a surname most prominently associated with New Zealand-born British actress Gina Bellman, known for her roles in television and film.
  • 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: Viterbi
Triple: [Andrew Viterbi, familyName, Viterbi]
Generated description
Viterbi is a surname most prominently associated with Andrew Viterbi, the Italian-American engineer and co-inventor of the Viterbi algorithm used in digital communications and error correction.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Viterbi
Target entity description: Viterbi is a surname most prominently associated with Andrew Viterbi, the Italian-American engineer and co-inventor of the Viterbi algorithm used in digital communications and error correction.
  • A. Viterbi algorithm
    The Viterbi algorithm is a dynamic programming method used to find the most likely sequence of hidden states in probabilistic models such as Hidden Markov Models, widely applied in fields like digital communications, speech recognition, and bioinformatics.
  • B. Baum–Welch algorithm
    The Baum–Welch algorithm is an expectation-maximization method used to train the parameters of hidden Markov models from observed data.
  • C. forward-backward algorithm
    The forward-backward algorithm is a dynamic programming method for computing posterior state probabilities in hidden Markov models, widely used in tasks like sequence labeling and speech recognition.
  • D. Hidden Markov Model
    A Hidden Markov Model is a statistical model that represents systems with unobserved (hidden) states generating observable outputs, widely used for sequence analysis tasks such as speech recognition, bioinformatics, and natural language processing.
  • E. Bellman
    Bellman is a surname most prominently associated with New Zealand-born British actress Gina Bellman, known for her roles in television and film.
  • 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_69d6ab4846e081908ee7bbd66a6d3459 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90440dd988190ae2b80367aceb6f7 completed April 10, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f654eb1881908d656009f1362ecf completed May 2, 2026, 1:04 p.m.
NEDg Description generation batch_69f5fd79da748190b3f0dd7d7a46314d completed May 2, 2026, 1:34 p.m.
NED2 Entity disambiguation (via description) batch_69f5fef775508190ab3be470821c5a50 completed May 2, 2026, 1:41 p.m.
Created at: April 8, 2026, 9:48 p.m.