تشخیص رابطه پرسشهای فارسی با ترکیب روشهای مستقیم و غیرمستقیم
عباس شاهینی شمس آبادی
1
(
دانشکده مهندسی کامپیوتر، دانشگاه اصفهان، اصفهان، ایران،
)
رضا رمضانی
2
(
دانشکده مهندسی کامپیوتر، دانشگاه اصفهان، اصفهان، ایران،
)
هادی خسروی فارسانی
3
(
دانشکده فنی و مهندسی، دانشگاه شهرکرد، شهرکرد، ایران،
)
محمدعلی نعمت بخش
4
(
دانشکده مهندسی کامپیوتر، دانشگاه اصفهان، اصفهان، ایران،
)
کلید واژه: پرسش- پاسخ فارسی, تشخیص رابطه, پایگاه دانش, پردازش زبان طبیعی.,
چکیده مقاله :
در این مطالعه برای مسأله پاسخ به سؤالهای فارسی با استفاده از دادههای پیوندی، زیرمسأله تشخیص رابطه برای سؤالهای تکرابطهای به تفصیل بررسی شده است. در این سؤالها، پاسخ از یک سهتایی به شکل <فاعل، گزارهنما، مفعول> استخراج میشود. این کار دارای دو مرحله اصلی میباشد: نگاشت نهاد و تشخیص رابطه. در مرحله اول، نهاد شناساییشده در سؤال به یک فاعل یا مفعول از یک سهتایی نگاشت شده و در مرحله دوم یک گزارهنما برای رابطه معنایی موجود در سؤال انتخاب میشود. در اکثر روشهای موجود پس از نگاشت نهاد، همه رابطههای آن نهاد در پایگاه دانش به عنوان رابطههای نامزد در مرحله تشخیص رابطه در نظر گرفته شده و در نهایت یکی از آنها انتخاب میشود. در این روشها اگر خطایی در مرحله نگاشت نهاد وجود داشته باشد به مرحله بعد منتشر شده و تشخیص رابطه به درستی انجام نمیشود. در این مطالعه برای رفع این وابستگی از ساختار سلسلهمراتبی رابطهها به منظور استخراج مستقیم رابطه سؤال بهره گرفته میشود. دقت روش پیشنهادی در زبان فارسی برای تشخیص مستقیم رابطه 72% و برای انتخاب بهترین رابطه نامزد (غیرمستقیم) 90% میباشد. این دقت با ترکیب دو روش مستقیم و غیرمستقیم به 94% افزایش پیدا کرده است
چکیده انگلیسی :
In this study, for the problem of answering Persian questions using linked data, the sub-problem of relation detection for single-relation questions has been investigated in detail. In these questions, the answer is extracted from a triple in the form of <subject, predicate, object>. This process has two main steps: entity linking and relation detection. In the first step, the entity identified in the question is mapped to a subject or object of a triple, and in the second step, a predicate is selected for the semantic relation in the question. In most existing methods, after entity linking, all relations of that entity in the knowledge base are considered as candidate relations, and finally one of them is selected as the final relation. In these methods, if there is an error in the entity linking step, it is propagated to the relation detection step. In this study, to solve this dependency, the hierarchical structure of relations is used in order to directly extract the relation of the question. The accuracy of the proposed method in Persian is 72% for direct relation detection and 90% for selecting the best candidate relation (indirect). The accuracy has increased to 94% by combining direct and indirect methods.
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