Torrent
E360072
Torrent is a municipality in eastern Spain that forms part of the metropolitan area of Valencia and is one of the largest towns in the Valencian Community.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Torrent canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T3448046 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Torrent Context triple: [Province of Valencia, contains, Torrent]
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A.
Interactive Proofs and the Hardness of Approximating Cliques
"Interactive Proofs and the Hardness of Approximating Cliques" is a seminal theoretical computer science paper that introduced powerful interactive proof techniques to show that finding near-maximum cliques in graphs is computationally intractable to approximate within strong bounds.
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B.
The Knowledge Complexity of Interactive Proof Systems
"The Knowledge Complexity of Interactive Proof Systems" is a seminal theoretical computer science paper that introduced the notion of zero-knowledge proofs, fundamentally shaping modern cryptography and complexity theory.
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C.
Swan constructed counterexamples over the rational numbers
Swan constructed counterexamples over the rational numbers refers to Richard G. Swan’s landmark result showing that certain invariant fields under finite group actions over the rational numbers are not rational, thereby disproving a general affirmative answer to Noether’s problem in this setting.
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D.
Dyson’s transform in number theory
Dyson’s transform in number theory is a combinatorial technique introduced by Freeman Dyson to manipulate and relate integer partitions, particularly in the study of partition identities and congruences.
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E.
Probably Approximately Correct learning (PAC learning)
Probably Approximately Correct (PAC) learning is a foundational framework in computational learning theory that formalizes what it means for an algorithm to efficiently learn a concept from examples with high probability and small error.
- 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: Torrent Target entity description: Torrent is a municipality in eastern Spain that forms part of the metropolitan area of Valencia and is one of the largest towns in the Valencian Community.
-
A.
Interactive Proofs and the Hardness of Approximating Cliques
"Interactive Proofs and the Hardness of Approximating Cliques" is a seminal theoretical computer science paper that introduced powerful interactive proof techniques to show that finding near-maximum cliques in graphs is computationally intractable to approximate within strong bounds.
-
B.
The Knowledge Complexity of Interactive Proof Systems
"The Knowledge Complexity of Interactive Proof Systems" is a seminal theoretical computer science paper that introduced the notion of zero-knowledge proofs, fundamentally shaping modern cryptography and complexity theory.
-
C.
Swan constructed counterexamples over the rational numbers
Swan constructed counterexamples over the rational numbers refers to Richard G. Swan’s landmark result showing that certain invariant fields under finite group actions over the rational numbers are not rational, thereby disproving a general affirmative answer to Noether’s problem in this setting.
-
D.
Dyson’s transform in number theory
Dyson’s transform in number theory is a combinatorial technique introduced by Freeman Dyson to manipulate and relate integer partitions, particularly in the study of partition identities and congruences.
-
E.
Probably Approximately Correct learning (PAC learning)
Probably Approximately Correct (PAC) learning is a foundational framework in computational learning theory that formalizes what it means for an algorithm to efficiently learn a concept from examples with high probability and small error.
- F. None of above. chosen
Statements (48)
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Torrent Description of subject: Torrent is a municipality in eastern Spain that forms part of the metropolitan area of Valencia and is one of the largest towns in the Valencian Community.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.