Triple

T13529874
Position Surface form Disambiguated ID Type / Status
Subject Tarjan's strongly connected components algorithm E323102 entity
Predicate relatedTo P37 FINISHED
Object Kosaraju's algorithm E1045495 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: Kosaraju's algorithm | Statement: [Tarjan's strongly connected components algorithm, relatedTo, Kosaraju's algorithm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kosaraju's algorithm
Context triple: [Tarjan's strongly connected components algorithm, relatedTo, Kosaraju's algorithm]
  • A. Kosaraju's algorithm chosen
    Kosaraju's algorithm is a graph traversal method used to efficiently find all strongly connected components in a directed graph.
  • B. Tarjan's strongly connected components algorithm
    Tarjan's strongly connected components algorithm is a classic linear-time graph algorithm that efficiently identifies all strongly connected components in a directed graph using depth-first search and low-link values.
  • C. Kruskal’s minimum spanning tree algorithm
    Kruskal’s minimum spanning tree algorithm is a classic greedy graph algorithm that builds a minimum spanning tree by repeatedly adding the smallest-weight edge that does not create a cycle, typically implemented efficiently using a union–find data structure.
  • D. union–find data structure
    The union–find data structure is an efficient algorithmic structure that maintains disjoint sets and supports fast union and find operations, widely used in graph algorithms such as Kruskal’s minimum spanning tree.
  • E. Bellman–Ford algorithm
    The Bellman–Ford algorithm is a graph shortest-path algorithm that can handle negative edge weights and detect negative cycles, often used in routing and network optimization.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafba2c308190873efd15dfe26358 completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75d95ce008190a915fe5865c38ee5 completed May 3, 2026, 2:37 p.m.
Created at: April 9, 2026, 9:44 p.m.