Automatic propbank generation for Turkish

Semantic role labeling (SRL) is an important task for understanding natural languages, where the objective is to analyse propositions expressed by the verb and to identify each word that bears a semantic role. It provides an extensive dataset to enhance NLP applications such as information retrieval, machine translation, information extraction, and question answering. However, creating SRL models are difficult. Even in some languages, it is infeasible to create SRL models that have predicate-argument structure due to lack of linguistic resources. In this paper, we present our method to create an automatic Turkish PropBank by exploiting parallel data from the translated sentences of English PropBank. Experiments show that our method gives promising results. © 2019 Association for Computational Linguistics (ACL).Publisher's Versio

Construction of a Turkish proposition bank

This paper describes our approach to developing the Turkish PropBank by adopting the semantic role-labeling guidelines of the original PropBank and using the translation of the English Penn-TreeBank as a resource. We discuss the semantic annotation process of the PropBank and language-specific cases for Turkish, the tools we have developed for annotation, and quality control for multiuser annotation. In the current phase of the project, more than 9500 sentences are semantically analyzed and predicate-argument information is extracted for 1330 verbs and 1914 verb senses. Our plan is to annotate 17,000 sentences by the end of 2017.This work was supported by Isik University BAP projects 14B206 and 15B201Publisher's Versio

Use of a Global Positioning System (GPS) to Manage Extensive Sheep Farming and Pasture Land

The terrestrial climate is not sufficient to produce enough food to meet the roughage needs of the animals benefiting from the pasture lands because of excessive and early grazing of those areas. Plant growth is adversely affected in pastures that are not uniformly grazed. Tracking animals using the Global Positioning System (GPS) is a very important factor in determining the uniform distribution of grazing animals in a pasture, increasing the utilization rate of the pasture, and saving costs and time. With GPS tracking systems, establishing more effective pasture-use systems by monitoring the feeding regimes of small animals, the status of feed in the pasture, and the grazing behavior of the animals would be possible. The present study aimed to investigate the use of GPS for pasture and herd management in Turkey in addition to using the traditional techniques.In the present study conducted in the village of Köseyusuflu in Yozgat Province in May 2017, 2018, and 2019, grazing benefits that were determined from the pasture containing two Akkaraman sheep herds were recorded using GPS tracking devices. The results suggested that the area covered with vegetation along the sheep’s spring grazing routes varied between 43.6 and 62.9%, the ratio of legumes in the pasture grass in the low grazing areas was between 0.50 and 4.10%, and the grass species were between 12.75 and 44.50%. We determined that the sheep in herd A traveled between 7.6 and 9.9 km, while the sheep in herd B traveled between 4.7 and 5.7 km daily, and the two herds grazed an average of between 122 and 254 daa

Comparison of the Effect of Different Anesthesia Maintenance on Hemodynamics in Coronary Artery Bypass Grafting Surgery: A Retrospective Cohort Study

Objective:General anesthesia management in coronary artery bypass graft surgery (CABGC) should preserve myocardial function, prevent ischemic damage, and maintain stable hemodynamics. There is not a universally accepted technique for anesthetic management during CABGC. Drugs or drug combinations and maintenance of infusions are decided based on the pathophysiological condition of the patient and the individual preference and experience of the anesthesiologist (1). Although there are many studies about an anesthesia induction in CABGC, studies about anesthetic maintenance are very limited. In this study, we compared the hemodynamic effects of three different methods that were used in anesthetic maintenance in CABGC.Method:The retrospective records of 108 patients in ASA II-III group who underwent elective CABGC were divided into 3 groups according to their anesthetic maintenance methods. Group I was maintained with 1-3% sevoflurane and fentanyl 4 mcg/kg/hour infusion, group II with propofol 1.5-4 mg/kg/hour and fentanyl 4 mcg/kg/hour infusion, and group III with propofol 1.5-4 mg/kg/hour and remifentanil infusion of 0.03 mg/kg/hour. Systolic blood pressure, diastolic blood pressure, mean arterial pressure (MAP) and heart rate (HR) were measured and recorded after induction (T0), after sternotomy (T1), after pericardiotomy (T2), 5 minutes after cardiopulmonary bypass (CPB) (T3), after thorax closure (T4), at the end of the operation (T5). The vasodilator requirements in the time period before CBP and the inotropic agent requirements after CPB were noted.Results:Data of 108 patients (88 men/20 women) were analyzed. Demographic characteristics of the patients were similar in all the groups. Statistical analysis was made among the groups depending on coronary artery bypass graft number, cross-clamp time, total fluid administration, total blood transfusion, total urine volume, inotropic agent requirement after CPB, postoperative central venous pressure, and pre- and postoperative lactate levels; however, there was no statistical difference. There was not change more than 20-25% in MAP and HR in group I than the others.Conclusion:Better hemodynamic results were achived with sevoflurane and fentanyl in the anesthetic maintenance of CABGC

A comparative ID migraine screener study in ophthalmology, ENT and neurology out-patient clinics

Migraine is more likely to be misdiagnosed in patients with comorbid diseases. Not only primary care physicians, but also specialists might misdiagnose it due to the lack of diagnostic criteria awareness. The ID migraine test is a reliable screening instrument that may facilitate and accelerate migraine recognition. This study aimed to compare the prevalence and characteristics of migraine in a large sample of patients admitted to clinics of ophthalmology (OC), ear, nose and throat diseases (ENTC) and neurology (NC), as well as to validate the use of the ID migraine test in OC and ENTC settings. This was a multicentre (11 cites) study of out-patients admitting either to NC, ENTC or OC of the study sites during five consecutive working days within 1 week. From each of the clinics, 100 patients were planned to be recruited. All recruited patients were interviewed and those having a headache complaint received an ID migraine test and were examined for headache diagnosis by a neurologist, blinded to the ID migraine test result. A total of 2625 subjects were recruited. Only 1.3% of OC patients and 5.4% of ENTC patients have been admitted with a primary complaint of headache, whereas the percentage of NC patients suffering from headache was 37.6%. Whereas 138 patients (19.3%) in OC, 154 (17.3%) in ENTC and 347 (34%) in NC were found to be ID migraine test positive, 149 patients (20.8%) in OC, 142 (16%) in ENTC and 338 (33.1%) in NC were diagnosed with migraine. The sensitivity, specificity, and positive and negative predictive ratios of the ID migraine test were found to be similar in all clinics. An important fraction of the patients admitted to NC, as well as to OC and ENTC, for headache and/or other complaints were found out to have migraine by means of a simple screening test. This study validated the ID migraine test as a sensitive and specific tool in OC and ENTC, encouraging its use as a screening instrument.Pfizer-Türkiy

Unsupervised morphological analysis using tries

This article presents an unsupervised morphological analysis algorithm to segment words into roots and affixes. The algorithm relies on word occurrences in a given dataset. Target languages are English, Finnish, and Turkish, but the algorithm can be used to segment any word from any language given the wordlists acquired from a corpus consisting of words and word occurrences. In each iteration, the algorithm divides words with respect to occurrences and constructs a new trie for the remaining affixes. Preliminary experimental results on three languages show that our novel algorithm performs better than most of the previous algorithms.Publisher's Versio

Comparison of Turkish proposition banks by frame matching

By indicating semantic relations between a predicate and its associated participants in a sentence and identifying the role-bearing constituents, SRL provides an extensive dataset to understand natural languages and to enhance several NLP applications such as information retrieval, machine translation, information extraction, and question answering. The availability of large resources and the development of statistical machine learning methods have increased the studies in the field of SRL. One of the widely-used semantic resources applied for multiple languages is PropBank. In this paper, PropBanks applied for Turkish are compared by checking semantic roles in the frame files of matched verb senses. As this integrated lexical resource for Turkish is aimed to be used in a multilingual resource along with English, creation of an inclusive lexical resource for Turkish is of great importance.Publisher's Versio