Triple
T15667126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christos H. Papadimitriou |
E377214
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object |
Papadimitriou–Yannakakis theorem
The Papadimitriou–Yannakakis theorem is a fundamental result in computational complexity theory that characterizes the complexity of certain optimization and approximation problems, particularly in relation to classes like NP and the theory of approximation algorithms.
|
E1170224
|
NE FINISHED |
How this triple was built (4 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: Papadimitriou–Yannakakis theorem | Statement: [Christos H. Papadimitriou, knownFor, Papadimitriou–Yannakakis theorem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Papadimitriou–Yannakakis theorem Context triple: [Christos H. Papadimitriou, knownFor, Papadimitriou–Yannakakis theorem]
-
A.
Papadimitriou: Computational Complexity
"Papadimitriou: Computational Complexity" is a widely used graduate-level textbook that systematically develops the theory of computational complexity, including classes like P and NP and the foundations of NP-completeness.
-
B.
Cook–Levin theorem
The Cook–Levin theorem is a foundational result in computational complexity theory that established the Boolean satisfiability problem (SAT) as the first NP-complete problem, launching the theory of NP-completeness.
-
C.
Babai–Fortnow–Lund–Safra–Szegedy theorem
The Babai–Fortnow–Lund–Safra–Szegedy theorem is a landmark result in computational complexity theory that characterizes the power of multi-prover interactive proofs by showing they capture exactly the class of nondeterministic exponential-time problems.
-
D.
“Inapproximability results for SAT and other problems”
“Inapproximability results for SAT and other problems” is a seminal theoretical computer science paper by Johan Håstad that establishes tight hardness-of-approximation bounds for satisfiability and related optimization problems using probabilistically checkable proofs.
-
E.
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.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Papadimitriou–Yannakakis theorem Triple: [Christos H. Papadimitriou, knownFor, Papadimitriou–Yannakakis theorem]
Generated description
The Papadimitriou–Yannakakis theorem is a fundamental result in computational complexity theory that characterizes the complexity of certain optimization and approximation problems, particularly in relation to classes like NP and the theory of approximation algorithms.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Papadimitriou–Yannakakis theorem Target entity description: The Papadimitriou–Yannakakis theorem is a fundamental result in computational complexity theory that characterizes the complexity of certain optimization and approximation problems, particularly in relation to classes like NP and the theory of approximation algorithms.
-
A.
Papadimitriou: Computational Complexity
"Papadimitriou: Computational Complexity" is a widely used graduate-level textbook that systematically develops the theory of computational complexity, including classes like P and NP and the foundations of NP-completeness.
-
B.
Cook–Levin theorem
The Cook–Levin theorem is a foundational result in computational complexity theory that established the Boolean satisfiability problem (SAT) as the first NP-complete problem, launching the theory of NP-completeness.
-
C.
Babai–Fortnow–Lund–Safra–Szegedy theorem
The Babai–Fortnow–Lund–Safra–Szegedy theorem is a landmark result in computational complexity theory that characterizes the power of multi-prover interactive proofs by showing they capture exactly the class of nondeterministic exponential-time problems.
-
D.
“Inapproximability results for SAT and other problems”
“Inapproximability results for SAT and other problems” is a seminal theoretical computer science paper by Johan Håstad that establishes tight hardness-of-approximation bounds for satisfiability and related optimization problems using probabilistically checkable proofs.
-
E.
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.
- F. None of above. chosen
Provenance (5 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f1151548190a14607e762686cb1 |
completed | April 16, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff67a22888819092ea521bbad7bcb7 |
completed | May 9, 2026, 4:58 p.m. |
| NEDg | Description generation | batch_69ff68fd16b88190a78772bcd0302189 |
completed | May 9, 2026, 5:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff6943d47881908c1634b43a6d6b96 |
completed | May 9, 2026, 5:05 p.m. |
Created at: April 10, 2026, 4:16 a.m.