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In this paper we present some preliminary remarks on the preparation of a morphosyntactically annotated treebank for Saho within the Universal Dependencies (UD) framework, an annotation scheme used in a large collection of corpora, where Cushitic languages are still marginally represented. We discuss some issues concerning tokenization, morphology, and syntax, with particular reference to cases where deviations from the descriptions proposed in the literature on Saho are deemed necessary, in order to accommodate Saho data within the UD architecture, and cases where some peculiarities of the Saho language require an expansion of the inventories put forward in UD. [ABSTRACT FROM AUTHOR]

Word segmentation, part-of-speech (POS) tagging, and syntactic parsing are three fundamental Chinese analysis tasks for Chinese language processing, which are also crucial for various downstream tasks such as machine translation and information extraction. To achieve high accuracy for these tasks, treebanks that contain sentences manually annotated with word segmentation, part-of-speech tags, and phrase structures are essential. Although there are large-scale Chinese treebanks in the news domain, such treebanks are unavailable in the scientific domain. This significantly limits the performance of Chinese language processing for scientific text. To address this problem, we annotate the 2nd version of the Chinese treebank in the scientific domain (SCTB-V2). SCTB-V2 contains 12,175 sentences annotated with word segmentation, part-of-speech tags, and phrase structures. We conducted Chinese analyses and machine translation experiments on SCTB-V2. The results show the effectiveness of SCTB-V2. We release this treebank to promote scientific Chinese language processing research http://nlp.ist.i.kyoto-u.ac.jp/EN/index.php?A%20Chinese%20Treebank%20 in%20Scientific%20Domain%20%28SCTB%29. [ABSTRACT FROM AUTHOR]

This paper presents the SAGT Turkish–German code-switching treebank, and observations and annotation challenges we encountered during its development. The treebank consists of transcriptions of bilingual conversations annotated with several layers: language IDs, lemmas, POS tags, morphological features, and dependency relations. The annotations follow the Universal Dependencies annotation scheme and the conventions used in monolingual treebanks as much as possible. We present and discuss a number of issues that arise because of the need for consistent multilingual annotation within a single treebank, as well as the informal language, which is where code-switching is observed most. Besides proposing solutions to these issues, we present some observations about code-switching phenomena that are only possible to observe in a data set with rich linguistic annotation. The treebank was annotated with a focus on quality of annotations through an iterative process of detecting and correcting annotation errors. We also present quantitative measures for indication of annotation quality. The code-switching treebank created in this study is released to the public through Universal Dependencies repositories. [ABSTRACT FROM AUTHOR]

This article presents a Universal Dependency (UD) annotation scheme for Mandarin Chinese, as well as the current UD Chinese HK treebank. Our focus is mainly on parts-of-speech tags and syntactic relations, with a quite large array of phenomena investigated. The main goal is to make transparent the linguistic consideration behind our annotation choices, and show how we articulated these choices with the criteria of Universal Dependencies. This scheme has been developed with reference to two other dependency schemes for this language, i.e. the Chinese Stanford Dependencies (Chang et al., 2009) and the Chinese Dependency Treebank (HIT-SCIR, 2010). We provide mappings between our scheme and the two others. The content of the UD Chinese HK treebank is discussed in relation to the other UD treebanks for Chinese, and the inter-annotator agreement on POS and dependency annotation is reported. Our proposed scheme is motivated by reasoned linguistic analysis, is suitable for cross-linguistic comparison, and produced a high level of agreement between annotators. [ABSTRACT FROM AUTHOR]

Copyright of Traitement Automatique des Langues is the property of Association pour le Traitement Automatique des Langues (ATALA) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Procesamiento del Lenguaje Natural is the property of Sociedad Espanola para el Procesamiento del Lenguaje Natural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The paper presents a novel and unified morphological description of numerals and pronouns, as compiled for the newest edition of the Prague Dependency Treebank (Prague Dependency Treebank – Consolidated 1.0) and its integral part the morphological dictionary MorfFlex. On the basis of considerable experience with real data annotation and the use of the morphological dictionary, particular changes were proposed. For both of the parts of speech a new set of subtypes was proposed, based mainly on the morphological criterion and its combination with semantic properties and other relevant features, such as definiteness in numerals and possessivity, reflexivity, and clitichood in pronouns. Each subtype has a specific value at the 2nd position of the morphological tag, which serves also as an indicator of the applicability of other tag categories. [ABSTRACT FROM AUTHOR]

We start with the assumption that (i) a corpus represents the use of language, i.e. linguistic performance, (ii) a rule-based grammar represents language as a system, i.e. linguistic competence, and (iii) corpus annotation represents the interface between the two. To detect and diagnose mismatches between the language use and the language system we use a constraint-based grammar run as a constraint solver on texts tagged and dependency-parsed by stochastic tools. The texts also have MWEs (multi-word expressions) identified and transformed into a constituency-based format before the grammar is applied. We describe the role and results of the grammar, and its use to check texts annotated with morphosyntactic categories, syntactic structure and information about the status of relevant expressions as MWEs. The grammar also employs lexical resources such as a valency lexicon and a database of MWEs to make the checking more accurate and the annotation more informative. The results are represented as typed feature structures where MWE-related information can be shared by lexical and phrasal nodes. This allows for the annotation of MWEs as lexical units, independently of their analysis in terms of syntactic structure. Focusing on the interplay of MWEs with their syntactic context we analyse a number of representative examples, pointing out the pros and cons of specific solutions and the whole approach.

This paper describes the construction and annotation of the Late Latin Charter Treebank, a set of three dependency treebanks (llct1, llct2 and llct3) which together contain 1,261 Early Medieval Latin documentary texts (i.e., original charters) written in Italy between ad 714 and 1000 (about 594,000 tokens). The paper focusses on matters which a linguistically or philologically inclined user of llct needs to know: the criteria on which the charters were selected, the special characteristics of the annotation types utilised, and the geographical and chronological distribution of the data. In addition to normal queries on forms, lemmas, morphology and syntax, complex philological research settings are enabled by the textual annotation layer of llct, which indicates abbreviated and damaged words, as well as the formulaic and non-formulaic passages of each charter. [ABSTRACT FROM AUTHOR]

A number of natural language processing tools for Urdu language processing have been developed in the past few years for word segmentation, part of speech tagging, chunking, named entity recognition and parsing. Corpora, especially treebanks, are essential data resources for language processing. This work presents the development and evaluation of an Urdu treebank, the CLE-UTB and a statistical parser. The treebank has been annotated with phrase structure annotation. Part of speech tagging has been performed semi-automatically by using an existing tagger and incorrect tags were corrected manually by annotators. The syntactic annotation has been performed in the Penn Treebank style to mark phrases. The annotation scheme also adds functional labels for grammatical roles. Currently, the treebank contains 7854 annotated sentences and 148,575 tokens. Completeness and correctness of the syntactic labels have been checked automatically after manual annotation. To ensure the annotation consistency of the resource, a grammar-based evaluation and an automatic consistency checking tool have been used to detect linguistically implausible constituents. The inter-annotator agreement is greater than 90%. We have developed a bidirectional long-short term memory (BiLSTM) based parser and a POS tagger which have been trained on the final version of the treebank. We have improved our results by training the word embeddings on a large Urdu text corpus. Our parser produced an f-score of 88.1% and the POS tagger performed with an accuracy of 96.3%. [ABSTRACT FROM AUTHOR]

This article presents an analysis of experiments with statistical and neural parsing techniques for Urdu, a widely spoken South Asian language. We demonstrate state of the art constituency parsing results for an Urdu treebank. Urdu is a morphologically rich and is characterized by free word order. Language representation (e.g. input type, lemmatization, word clusters), part of speech tag set, phrase labels and the size of a training corpus are crucial for parsing such languages. In this article, probabilistic context-free grammars, data-oriented parsing, and recursive neural network based models have been experimented with several linguistic features which show improvements in the parsing results. Features include syntactic sub-categorization of POS tags, empirically learned horizontal and vertical markovizations and lexical head words. These features enable dependency information for case markers and add phrasal and lexical context to the parse trees. The data-oriented parsing and recursive neural network model give an f-score of 87.1 by considering gold POS tags in the test set, on textual input, they show a performance with f-scores of 83.4 and 84.2, respectively. To overcome the issue of data sparsity due to the morphological richness, lemmatization and unsupervised word clustering have been performed. A treebank should cover most probable word orders of the language so that models can learn various orders accurately. To analyze the order coverage of the treebank and learning capability of different parsers, a test set has been prepared conditioning different word orders. This test set is evaluated with the best performing parsing models and with gold POS tags, f-scores are above 90 and on textual input, the average f-score is 87.6.

This paper takes a corpus-based approach and examines the linguistic properties of two Korean nominalizers -(u)m and -ki. From the Sejong Treebank corpus, all the sentences with -(u)m and -ki are extracted. Twenty linguistic factors are manually encoded into the extracted sentences. Then, all the encoded data are statistically analyzed with (binary) logistic regression. Although we take a monofactorial analysis, we obtain a good statistical model whose C value is 0.956. Through the analysis, the followings are observed: (i) -(u)m and -ki are used with the ratio of 1:9 in Korean, (ii) among twenty linguistic factors, only ten factors are statistically significant, and (iii) not only the verbs which take -(u)m and -ki as a complement but also the verbs which merge with these two nominalizers also play important roles in the determination of nominalizers. [ABSTRACT FROM AUTHOR]

ObjectiveTo create annotated clinical narratives with layers of syntactic and semantic labels to facilitate advances in clinical natural language processing (NLP). To develop NLP algorithms and open source components.MethodsManual annotation of a clinical narrative corpus of 127 606 tokens following the Treebank schema for syntactic information, PropBank schema for predicate-argument structures, and the Unified Medical Language System (UMLS) schema for semantic information. NLP components were developed.ResultsThe final corpus consists of 13 091 sentences containing 1772 distinct predicate lemmas. Of the 766 newly created PropBank frames, 74 are verbs. There are 28 539 named entity (NE) annotations spread over 15 UMLS semantic groups, one UMLS semantic type, and the Person semantic category. The most frequent annotations belong to the UMLS semantic groups of Procedures (15.71%), Disorders (14.74%), Concepts and Ideas (15.10%), Anatomy (12.80%), Chemicals and Drugs (7.49%), and the UMLS semantic type of Sign or Symptom (12.46%). Inter-annotator agreement results: Treebank (0.926), PropBank (0.891-0.931), NE (0.697-0.750). The part-of-speech tagger, constituency parser, dependency parser, and semantic role labeler are built from the corpus and released open source. A significant limitation uncovered by this project is the need for the NLP community to develop a widely agreed-upon schema for the annotation of clinical concepts and their relations.ConclusionsThis project takes a foundational step towards bringing the field of clinical NLP up to par with NLP in the general domain. The corpus creation and NLP components provide a resource for research and application development that would have been previously impossible.

In this paper we introduce an extended version of the Vedic Treebank (vtb, Hellwig et al. 2020) which comes along with revisited and extended annotation guidelines. In order to assess the quality of our annotations as well as the usability and limits of the guidelines we performed an inter-annotator agreement test. The results show that agreement between annotators is hampered by various factors, most prominently by insufficient understanding of the content because of the cultural and temporal gap and incomplete knowledge of Vedic grammar. An in-depth discussion of disagreeing annotations demonstrates that the setup of the workflow, too, has a major influence on inter-annotator agreement. We suggest some measures that can help increase the transparency and annotation consistency according to current knowledge of the language when annotating Vedic Sanskrit, or ancient language varieties in general. [ABSTRACT FROM AUTHOR]

This article, which is the result of the master's research, presents the keyword extraction of Euripides' Greek tragedy called Heracles, associated with the treebanking in order to determine themes and formal aspects of the work. This, first Heracles was compared statistically with the other eighteen works by Euripides, without lemmatization. Subsequently, sections containing the keywords were selected for the purpose of analyzing them morphosyntactically in treebank. The results showed four central themes in the tragedy as the characters, the family ties, the characterization of Heracles through their weapons and labors, and his madness. [ABSTRACT FROM AUTHOR]

We start with the assumption that (i) a corpus represents the use of language, i.e. linguistic performance, (ii) a rule-based grammar represents language as a system, i.e. linguistic competence, and (iii) corpus annotation represents the interface between the two. To detect and diagnose mismatches between the language use and the language system we use a constraint-based grammar run as a constraint solver on texts tagged and dependency-parsed by stochastic tools. The texts also have MWEs (multi-word expressions) identified and transformed into a constituency-based format before the grammar is applied. We describe the role and results of the grammar, and its use to check texts annotated with morphosyntactic categories, syntactic structure and information about the status of relevant expressions as MWEs. The grammar also employs lexical resources such as a valency lexicon and a database of MWEs to make the checking more accurate and the annotation more informative. The results are represented as typed feature structures where MWE-related information can be shared by lexical and phrasal nodes. This allows for the annotation of MWEs as lexical units, independently of their analysis in terms of syntactic structure. Focusing on the interplay of MWEs with their syntactic context we analyse a number of representative examples, pointing out the pros and cons of specific solutions and the whole approach. [ABSTRACT FROM AUTHOR]

Copyright of Traitement Automatique des Langues is the property of Association pour le Traitement Automatique des Langues (ATALA) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Language: Meaning & Form / Valoda: Nozime un Forma is the property of University of Latvia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)