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Record W3040098638 · doi:10.1109/re48521.2020.00049

Symboleo: Towards a Specification Language for Legal Contracts

2020· article· en· W3040098638 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicLogic, Reasoning, and Knowledge
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceExecutableDesign by contractSpecification languageFormal specificationSmart contractProgramming languageOntologySoftware engineeringSemantics (computer science)AxiomLanguage Of Temporal Ordering SpecificationComputer securitySoftwareSoftware developmentDatabase transaction

Abstract

fetched live from OpenAlex

Legal contracts specify the terms and conditions (in essence, requirements) that apply to business transactions. Smart contracts are software systems that monitor and control the execution of contracts to ensure compliance. This paper proposes a formal specification language for contracts, called Symboleo, where contracts consist of collections of obligations and powers that define the legal contract's compliant executions. The formal semantics of Symboleo is based on an extension of an ontology for Law and is described in terms of logical axioms on statecharts that describe the lifetimes of contracts, obligations and powers. Our proposal includes a preliminary evaluation through the specification of a real life-inspired Sale-of-Goods contract, with a prototype execution engine. We envision this language to enable formally verifying contracts to detect requirements-level issues and to generate executable smart contracts (e.g., on blockchain technology).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.264
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations54
Published2020
Admission routes1
Has abstractyes

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