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Passing a USA National Bar Exam – a First Experiment

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Bar exams provide are a key watershed by which legal professionals demonstrate their knowledge of the law and its application. Passing the bar entitles one to practice the law in a given jurisdiction. The bar provides a excellent benchmark for the performance of legal information systems since passing the bar would arguably signal that the system has acquired key aspects of legal reason on a par with a human lawyer. The paper presents a first experiment with actual bar exam material, treating it as a form of textual entailment from the question to an answer. The Gold Standard is provided by the company which provides the bar exam. The paper reports a textual entailment student on a US bar exam, running ‘out of the box’ the Excitement Open Platform for textual entailment. The results and evaluation show that the tool can identify wrong answers (non-entailment) with a high F1 score, it performs poorly in identifying the correct answer (entailment). The results provide a baseline performance measure against which to evaluate future improvements. The reasons for the poor performance are examined, and proposals are made to augment the tool in the future.
Title: Passing a USA National Bar Exam – a First Experiment
Description:
Bar exams provide are a key watershed by which legal professionals demonstrate their knowledge of the law and its application.
Passing the bar entitles one to practice the law in a given jurisdiction.
The bar provides a excellent benchmark for the performance of legal information systems since passing the bar would arguably signal that the system has acquired key aspects of legal reason on a par with a human lawyer.
The paper presents a first experiment with actual bar exam material, treating it as a form of textual entailment from the question to an answer.
The Gold Standard is provided by the company which provides the bar exam.
The paper reports a textual entailment student on a US bar exam, running ‘out of the box’ the Excitement Open Platform for textual entailment.
The results and evaluation show that the tool can identify wrong answers (non-entailment) with a high F1 score, it performs poorly in identifying the correct answer (entailment).
The results provide a baseline performance measure against which to evaluate future improvements.
The reasons for the poor performance are examined, and proposals are made to augment the tool in the future.

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