Hence, Socrates is mortal: A Benchmark for Natural Language Syllogistic Reasoning
Bibliographic record
Abstract
Syllogistic reasoning, a typical form of deductive reasoning, is a critical capability widely required in natural language understanding tasks, such as text entailment and question answering.To better facilitate research on syllogistic reasoning, we develop a benchmark called SYLLOBASE that differs from existing syllogistic datasets in three aspects: (1) Covering a complete taxonomy of syllogism reasoning patterns; (2) Containing both automatically and manually constructed samples; and (3) Involving both the generation and understanding tasks.We automatically construct 50k template-based syllogism samples by mining syllogism patterns from Wikidata and ConceptNet.To improve our dataset's naturalness and challenge, we apply GPT-3 to paraphrase the templatebased data and further manually rewrite 1,000 samples as the test set.State-of-the-art pretrained language models can achieve the best generation ROUGE-L of 38.72 by T5 and the best multi-choice accuracy of 72.77% by RoBERTa on SYLLOBASE, which indicates the great challenge of learning diverse syllogistic reasoning types on SYLLOBASE.Our datasets are released at https://github.com/ casually-PYlearner/SYLLOBASE.ConceptNet An open, multilingual knowledge graph (1) Triplet Extraction (Section 3.1) (2) Syllogism Construction (Section 3.2) (3) Paraphrasing (GPT-3) (Section 3.3) ① (human, capable of, mortal), (Socrates, is a, human) ② (meteoritics, subclass of, astronomy), (astronomy, subclass of, exact science) Premise 1: All human are mortal.Premise 1: Some astronomy are meteoritics.Premise 2: All Socrates are human.Premise 2: All astronomy are exact science.Conclusion: All Socrates are mortal.Conclusion: Some exact science are meteoritics Pattern: All 𝑚 are 𝑝, all 𝑠 are m ⟶ All 𝑠 are 𝑝.Pattern: Some 𝑚 are 𝑝, all 𝑚 are 𝑠 ⟶ Some 𝑠 are 𝑝.Premise 1: It is a fact that all human beings are mortal.Premise 2: Socrates was a classic Greek philosopher credited as one of the founders of Western philosophy.Conclusion: It is true that Socrates was mortal as well.Premise 1: Meteoritics, which is a specific type of astronomy, involves the study of meteors and meteorites.Premise 2: Astronomy is an exact science meaning precise observation and mathematical calculations are implemented.Conclusion: Some precise sciences are used to further expand upon knowledge of meteorites and meteors.Table 2: Examples of syllogisms from our test set.Categorical Syllogism Premise 1: Carbon dioxide is a chemical compound.Premise 2: Chemical compounds are considered pure substances.Conclusion: Pure substances include carbon dioxide.Hypothetical Syllogism Premise 1: When you make progress in your project, you may want to celebrate.Premise 2: Having a party is a good choice if you want to celebrate.Conclusion: You may want to have a party if you achieve great progress in your project.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.017 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".