Search Results (6)

This article is about the cross-linguistic universality of the so-called Universal Sorter, where a noun N means ‘kind of N’. We discuss two restrictions in two Slavic languages which are absent from English, pertaining to perfective verbs and numerically modified count nouns. We establish, first with introspective judgments (for Czech) and then experimentally (for Slovak), that both restrictions are present in a way which supports our analysis of the first restriction as stemming from Slavic, unlike English, having perfective verbs which force a completive reading of an incremental theme. Full article

One of the traditional observations about English derivational morphology is that prefixes behave differently from suffixes and are rather close to lexemes. A word-based analysis of prefixes based on this observation has been proposed, but it faces a challenge raised by the seemingly category-changing property of the comparative verb-forming prefix out-. This study aims to solve this problem in a framework that enriches the traditional generative word-based morphology with the concept of the Abstract Lexical Unit. In analyzing data, I pay attention to the degree semantics of comparative out-prefixed verbs and show that the so-called “denominal or deadjectival” out-verbs are produced as hyponyms of already existing out-verbs with sparse semantics. A pseudonym experiment demonstrates that this type of out-verb has a number/rank/action comparative interpretation, and the nouns or adjectives that occupy the head position further specify the object that is counted. The problematic type is related to its base word via head replacement rather than concatenative affixation. Drawing on these new perspective and observations, this paper shows that the traditional finding about the status of English prefixes can be maintained in a word-based approach. Full article

Educated by generations of grammarians who state that the term sanguis (blood) is used only in the singular, Fathers of the Church, exegetes, and commentators were confronted with about twenty scriptural, essentially veterotestimentary tokens where sanguis is used in the plural. Justifications for this particular use appear throughout the commentaries. My study will attempt to answer a series of questions. Which passages interested the commentators the most and why? Which grammarians were involved and in what respect? What kind of justifications were provided? Was their interest purely hermeneutic or did the exegetes aim to preserve a state inherited from scrupulous translations? Were the passages treated in isolation or set in resonance? Does this assessment of the commentaries allow us to identity filiations? It will also be seen that this matter is another piece of the puzzle in the relationship between grammar and faith. Full article

Preoperative language mapping with navigated transcranial magnetic stimulation (nTMS) is currently based on the disruption of performance during object naming. The resulting cortical language maps, however, lack accuracy when compared to intraoperative mapping. The question arises whether nTMS results can be improved, when another language task is considered, involving verb retrieval in sentence context. Twenty healthy German speakers were tested with object naming and a novel action naming task during nTMS language mapping. Error rates and categories in both hemispheres were compared. Action naming showed a significantly higher error rate than object naming in both hemispheres. Error category comparison revealed that this discrepancy stems from more lexico-semantic errors during action naming, indicating lexico-semantic retrieval of the verb being more affected than noun retrieval. In an area-wise comparison, higher error rates surfaced in multiple right-hemisphere areas, but only trends in the left ventral postcentral gyrus and middle superior temporal gyrus. Hesitation errors contributed significantly to the error count, but did not dull the mapping results. Inclusion of action naming coupled with a detailed error analysis may be favorable for nTMS mapping and ultimately improve accuracy in preoperative planning. Moreover, the results stress the recruitment of both left- and right-hemispheric areas during naming. Full article

The purpose of the current study was to explore if and how additional-language learners may show changes in phraseological patterns over the course of a stay in a target-language environment. In particular, we focused on noun+adjective combinations produced by a group of additional-language speakers of French at three points in time, spanning 21 months and including an academic year in France. We extracted each combination from a longitudinal corpus and determined frequency counts and two strength-of-association measures (Mutual information [MI] score and Log Dice) for each combination. Separate analyses were conducted for frequency and the strength-of-association measures, revealing that phraseological patterns are significantly predicted by adjective position in the case of all three measures, and that MI scores showed significant change over time. We interpret the results in light of past research that has reported contradictory findings concerning change in phraseological patterns following an immersion experience. Full article

Words have different meanings (i.e., senses) depending on the context. Disambiguating the correct sense is important and a challenging task for natural language processing. An intuitive way is to select the highest similarity between the context and sense definitions provided by a large lexical database of English, WordNet. In this database, nouns, verbs, adjectives, and adverbs are grouped into sets of cognitive synonyms interlinked through conceptual semantics and lexicon relations. Traditional unsupervised approaches compute similarity by counting overlapping words between the context and sense definitions which must match exactly. Similarity should compute based on how words are related rather than overlapping by representing the context and sense definitions on a vector space model and analyzing distributional semantic relationships among them using latent semantic analysis (LSA). When a corpus of text becomes more massive, LSA consumes much more memory and is not flexible to train a huge corpus of text. A word-embedding approach has an advantage in this issue. Word2vec is a popular word-embedding approach that represents words on a fix-sized vector space model through either the skip-gram or continuous bag-of-words (CBOW) model. Word2vec is also effectively capturing semantic and syntactic word similarities from a huge corpus of text better than LSA. Our method used Word2vec to construct a context sentence vector, and sense definition vectors then give each word sense a score using cosine similarity to compute the similarity between those sentence vectors. The sense definition also expanded with sense relations retrieved from WordNet. If the score is not higher than a specific threshold, the score will be combined with the probability of that sense distribution learned from a large sense-tagged corpus, SEMCOR. The possible answer senses can be obtained from high scores. Our method shows that the result (50.9% or 48.7% without the probability of sense distribution) is higher than the baselines (i.e., original, simplified, adapted and LSA Lesk) and outperforms many unsupervised systems participating in the SENSEVAL-3 English lexical sample task. Full article