Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userOn the Quantum-like Contextuality of Ambiguous Phrases
على السياق الكمي مثل العبارات الغامضة
521
0 0
0.0
(
0
)
Created by
Shamra Editor
Ask ChatGPT about the research
اللغة هي السياق مثل المعاني من الكلمات تعتمد على سياقاتها.السياق هو، من المفهوم المحدد جيدا في ميكانيكا الكم حيث يعتبر موردا كبيرا لحسابات الكمومية.نحن نحقق في ما إذا كانت اللغة الطبيعية تعرض أي من الميزات السياقية الميكانيكية الكمومية.نظير على أنه يمكن تصميم مجموعات المعنى في عبارات غامضة في الإطار النظري للحز في السياق الكمومي، حيث يمكن أن تصبح حيازة حيازة.باستخدام إطار عمل السياق من قبل الافتراضي (CBD)، نستكشف المتغيرات الاحتمالية لهذه وإظهار أن سياق CBD هو ممكن أيضا.
Language is contextual as meanings of words are dependent on their contexts. Contextuality is, concomitantly, a well-defined concept in quantum mechanics where it is considered a major resource for quantum computations. We investigate whether natural language exhibits any of the quantum mechanics' contextual features. We show that meaning combinations in ambiguous phrases can be modelled in the sheaf-theoretic framework for quantum contextuality, where they can become possibilistically contextual. Using the framework of Contextuality-by-Default (CbD), we explore the probabilistic variants of these and show that CbD-contextuality is also possible.
References used
https://aclanthology.org/
rate research
Read More
Human-assisting systems such as dialogue systems must take thoughtful, appropriate actions not only for clear and unambiguous user requests, but also for ambiguous user requests, even if the users themselves are not aware of their potential requireme
nts. To construct such a dialogue agent, we collected a corpus and developed a model that classifies ambiguous user requests into corresponding system actions. In order to collect a high-quality corpus, we asked workers to input antecedent user requests whose pre-defined actions could be regarded as thoughtful. Although multiple actions could be identified as thoughtful for a single user request, annotating all combinations of user requests and system actions is impractical. For this reason, we fully annotated only the test data and left the annotation of the training data incomplete. In order to train the classification model on such training data, we applied the positive/unlabeled (PU) learning method, which assumes that only a part of the data is labeled with positive examples. The experimental results show that the PU learning method achieved better performance than the general positive/negative (PN) learning method to classify thoughtful actions given an ambiguous user request.
We revisit the topic of translation direction in the data used for training neural machine translation systems and focusing on a real-world scenario with known translation direction and imbalances in translation direction: the Canadian Hansard. Accor
ding to automatic metrics and we observe that using parallel data that was produced in the matching'' translation direction (Authentic source and translationese target) improves translation quality. In cases of data imbalance in terms of translation direction and we find that tagging of translation direction can close the performance gap. We perform a human evaluation that differs slightly from the automatic metrics and but nevertheless confirms that for this French-English dataset that is known to contain high-quality translations and authentic or tagged mixed source improves over translationese source for training.
Generating high quality question-answer pairs is a hard but meaningful task. Although previous works have achieved great results on answer-aware question generation, it is difficult to apply them into practical application in the education field. Thi
s paper for the first time addresses the question-answer pair generation task on the real-world examination data, and proposes a new unified framework on RACE. To capture the important information of the input passage we first automatically generate (rather than extracting) keyphrases, thus this task is reduced to keyphrase-question-answer triplet joint generation. Accordingly, we propose a multi-agent communication model to generate and optimize the question and keyphrases iteratively, and then apply the generated question and keyphrases to guide the generation of answers. To establish a solid benchmark, we build our model on the strong generative pre-training model. Experimental results show that our model makes great breakthroughs in the question-answer pair generation task. Moreover, we make a comprehensive analysis on our model, suggesting new directions for this challenging task.
With the advent of contextualized embeddings, attention towards neural ranking approaches for Information Retrieval increased considerably. However, two aspects have remained largely neglected: i) queries usually consist of few keywords only, which i
ncreases ambiguity and makes their contextualization harder, and ii) performing neural ranking on non-English documents is still cumbersome due to shortage of labeled datasets. In this paper we present SIR (Sense-enhanced Information Retrieval) to mitigate both problems by leveraging word sense information. At the core of our approach lies a novel multilingual query expansion mechanism based on Word Sense Disambiguation that provides sense definitions as additional semantic information for the query. Importantly, we use senses as a bridge across languages, thus allowing our model to perform considerably better than its supervised and unsupervised alternatives across French, German, Italian and Spanish languages on several CLEF benchmarks, while being trained on English Robust04 data only. We release SIR at https://github.com/SapienzaNLP/sir.
Paper Find the possibility of interpreting the vertical electrical sounding curves in real field , having been reached resistivity virtual account through the equation is valid for all configurations
V(r)=I/2 πr[C1pn+T() + C2p1]
Search results
provide a lot of time and effort in processing and interpretation of the geoelectrical data , and reflected positively on the interpretation of the vertical electrical sounding academic and an applied.
suggested questions
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
