Triple
T19108812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eulerian trail |
E467732
|
entity |
| Predicate | algorithmicConstruction |
P79475
|
FINISHED |
| Object | Fleury's algorithm |
—
|
NE NERFINISHED |
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: Fleury's algorithm | Statement: [Eulerian trail, algorithmicConstruction, Fleury's algorithm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fleury's algorithm Context triple: [Eulerian trail, algorithmicConstruction, Fleury's algorithm]
-
A.
Dijkstra
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.
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.
-
C.
Floyd–Warshall algorithm
The Floyd–Warshall algorithm is a classic dynamic programming method in computer science for efficiently computing shortest paths between all pairs of vertices in a weighted graph, even when negative edge weights are present.
-
D.
Dijkstra's shortest path algorithm
Dijkstra's shortest path algorithm is a classic graph algorithm that efficiently computes the minimum-cost paths from a single source vertex to all other vertices in a weighted graph with non-negative edge weights.
-
E.
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.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fleury's algorithm Target entity description: Fleury's algorithm is a classical graph-theoretic procedure for systematically finding an Eulerian trail by repeatedly choosing edges that are not bridges unless necessary.
-
A.
Dijkstra
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.
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.
-
C.
Floyd–Warshall algorithm
The Floyd–Warshall algorithm is a classic dynamic programming method in computer science for efficiently computing shortest paths between all pairs of vertices in a weighted graph, even when negative edge weights are present.
-
D.
Dijkstra's shortest path algorithm
Dijkstra's shortest path algorithm is a classic graph algorithm that efficiently computes the minimum-cost paths from a single source vertex to all other vertices in a weighted graph with non-negative edge weights.
-
E.
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.
- F. None of above. chosen
Provenance (2 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_69d8dd06a26481908039e2a1bae8c597 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e391f00c8190881a5977dd3728ed |
completed | April 20, 2026, 8:28 a.m. |
Created at: April 10, 2026, 12:04 p.m.