Triple

T10700881
Position Surface form Disambiguated ID Type / Status
Subject Viterbi algorithm E252270 entity
Predicate relatedTo P37 FINISHED
Object Dijkstra algorithm E79781 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: Dijkstra algorithm | Statement: [Viterbi algorithm, relatedTo, Dijkstra algorithm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dijkstra algorithm
Context triple: [Viterbi algorithm, relatedTo, Dijkstra algorithm]
  • A. Dijkstra chosen
    Dijkstra is a renowned Dutch computer scientist best known for his pioneering work in algorithms, including Dijkstra's shortest path algorithm, and for his influential contributions to programming methodology and software engineering.
  • B. Kruskal
    Kruskal is a surname most prominently associated with American mathematician Martin David Kruskal, known for his work in soliton theory and nonlinear science.
  • C. Cristian's algorithm
    Cristian's algorithm is a clock synchronization method in distributed systems that estimates accurate time on client machines by querying a time server and adjusting for message delays.
  • D. BFS
    BFS is the three-letter IATA airport code assigned to Belfast International Airport in Northern Ireland.
  • E. DFS
    DFS is the commonly used abbreviation for the New York State Department of Financial Services, the state agency that regulates financial services and products in New York.
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fd8bb7408190a350840e1df3b910 completed April 9, 2026, 1:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69d998ed78e481908537ae10d55e6f65 completed April 11, 2026, 12:42 a.m.
Created at: April 8, 2026, 9:12 p.m.