Triple
T23461701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John E. Hopcroft |
E568994
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | Hopcroft–Karp 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: Hopcroft–Karp algorithm | Statement: [John E. Hopcroft, knownFor, Hopcroft–Karp algorithm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hopcroft–Karp algorithm Context triple: [John E. Hopcroft, knownFor, Hopcroft–Karp algorithm]
-
A.
Gale–Shapley algorithm
The Gale–Shapley algorithm is a foundational procedure in mathematics and computer science that computes stable matchings between two equally sized sets, such as students and schools or men and women in the stable marriage problem.
-
B.
Fleury's algorithm
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.
-
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.
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.
-
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. 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: Hopcroft–Karp algorithm Target entity description: The Hopcroft–Karp algorithm is a classic efficient algorithm in computer science for finding maximum matchings in bipartite graphs.
-
A.
Gale–Shapley algorithm
The Gale–Shapley algorithm is a foundational procedure in mathematics and computer science that computes stable matchings between two equally sized sets, such as students and schools or men and women in the stable marriage problem.
-
B.
Fleury's algorithm
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.
-
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.
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.
-
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. 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_69e2458ebd808190b3298163132cfb0b |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a69bc200819096ed2baf25cdee4f |
completed | April 29, 2026, 6:35 a.m. |
Created at: April 17, 2026, 5:54 p.m.