Triple
T2268072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew Viterbi |
E50192
|
entity |
| Predicate | hasAlgorithmNamedAfter |
P37563
|
FINISHED |
| Object | Viterbi algorithm |
E252270
|
NE FINISHED |
How this triple was built (3 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 algorithm | Statement: [Andrew Viterbi, hasAlgorithmNamedAfter, Viterbi algorithm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viterbi algorithm Context triple: [Andrew Viterbi, hasAlgorithmNamedAfter, Viterbi algorithm]
-
A.
Viterbi algorithm
chosen
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.
Berlekamp–Massey algorithm
The Berlekamp–Massey algorithm is a key algorithm in coding theory and cryptography used to efficiently determine the shortest linear feedback shift register that generates a given binary sequence.
-
C.
Thompson's algorithm
Thompson's algorithm is a classic computer science method for converting regular expressions into nondeterministic finite automata (NFAs), widely used in pattern matching and lexical analysis.
-
D.
Marzullo's algorithm
Marzullo's algorithm is a method for selecting the most likely correct time interval from multiple, possibly conflicting time sources, commonly used in clock synchronization systems.
-
E.
Knuth–Morris–Pratt algorithm
The Knuth–Morris–Pratt algorithm is a classic linear-time string-searching algorithm that efficiently finds occurrences of a pattern within a text by precomputing a prefix function to avoid redundant comparisons.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlgorithmNamedAfter Context triple: [Andrew Viterbi, hasAlgorithmNamedAfter, Viterbi algorithm]
-
A.
hasTheoremNamedAfter
Indicates that a theorem is named in honor of or after a particular person or entity.
-
B.
hasAwardNamedAfter
Indicates that an entity has an award that is named in honor of another entity.
-
C.
hasLawNamedAfter
Indicates that a law or piece of legislation is named in honor of, or directly after, a particular entity.
-
D.
hasSymbolNamedAfter
Indicates that one entity has a symbol whose name is derived from or dedicated to another entity.
-
E.
hasPlaceNamedAfter
Indicates that one place is named in honor of or derived from the name of another place.
- 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_69a88b01e0048190ba96431b5f990ba9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc2ea65288190bc8644a07a11dfa9 |
completed | March 7, 2026, 6:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae894a20e0819097f08959f7a062ef |
completed | March 9, 2026, 8:48 a.m. |
| PD | Predicate disambiguation | batch_69abbdb592588190ac1ef5e8c54575b1 |
completed | March 7, 2026, 5:55 a.m. |
| PDg | Predicate description generation | batch_69abc2e97eb0819084acb26cfa4e3946 |
completed | March 7, 2026, 6:17 a.m. |
Created at: March 4, 2026, 7:48 p.m.