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Almost entirely overlooked throughout the 20th century, neglected by contemporary medical manuals, the clitoris has gradually returned centre stage thanks to Western feminism.

Preliminary biostratigraphic and geochronological results obtained from a 44 m-long core drilled on the northern coast of Mayaguana Island (SE Bahamas) show that the topmost layers of the core date from the Burdigalian (Early Miocene), whereas the deepest units are of Chattian (Late Oligocene) or Aquitanian (Earliest Miocene) age. Accordingly, the platform aggraded 44 m of sediments in a 10 to 3 my time span, from the Chattian/Aquitanian to the Burdigalian, whereas previous surface investigations of the island showed that only 11 m of carbonates were accumulated in a 17 my-long period, between the Burdigalian and the Early Pleistocene. This new record shows that the accumulation rate of the Mayaguana Bank was much higher during the Late Paleogene/Early Miocene than during the time interval from the Middle Miocene to the Pleistocene. This decrease is likely due to vertical tectonic motions related to the late phases of the Cuban orogeny which reduced accommodation on the platform top. These results designate the Mayaguana Bank as an accurate gauge to record the elevation of sea-level highstands during the Neogene

The most salient geological features observed during a recent reconnaissance trip to Crooked Island, SE Bahamas, include: (1) altered bioclastic calcarenites of probable Early Pleistocene age; and (2) an elevated intertidal notch carved in last interglacial deposits, indicating that sea level peaked at a higher elevation than previously estimated during that time period. Four main lithostratigraphic units were identified on Crooked Island: (1) highly weathered bioclastic calcarenites that yielded unreliable alloisoleucine/isoleucine (A/I) ratios, and two valid 87Sr/86Sr ratios averaging 0.709147; (2) well-lithified bioclastic/peloidal eolianites, forming low sea cliffs, that gave one A/I ratio of 0.523; (3) a complex and extensive unit including scarce coral framestone, exposed up to +1.2 m above sea level, and oolitic-peloidal calcarenites deposited in subtidal, beach, and eolian environments that yielded A/I ratios averaging 0.411 (n=5); and (4) poorly lithified bioclastic beach ridges congruent with modern sea level. Moreover, a prominent ridge along the north coast of the island shows, at +11 m above sea level, an intertidal notch carved in Unit 3 eolianite and filled by Unit 3 beach facies. Units 4, 3 and 2 can be compared, respectively, to the Rice Bay (Holocene), the Grotto Beach (Late Pleistocene) and the Owl's Hole (Middle Pleistocene) formations, previously identified on many other Bahamian islands. Of probable Early Pleistocene age (between 0.6 and 1 Ma), Unit 1 could represent the lowermost part of the Owl's Hole Formation and the top of the underlying, mostly marine Misery Point Formation recently discovered on Mayaguana. The unequivocal occurrence of an intertidal notch carved in, and sealed by, last-interglacial deposits at +11 m shows that the peak elevation reached by sea level during that time interval was much higher than previously assessed. Finally, stratigraphic units decrease in age from N to S, suggesting that the island grew differently than other Bahamian islands or, alternatively, that the northern margin of the Crooked-Acklins bank collapsed in a recent past.

When developing NLP tools for low-resource languages, one is often confronted with the lack of annotated data. We propose to circumvent this bottleneck by training a supervised HMM tagger on a closely related language for which annotated data are available, and translating the words in the tagger parameter files into the low-resource language. The translation dictionaries are created with unsupervised lexicon induction techniques that rely only on raw textual data. We obtain a tagging accuracy of up to 89.08% using a Spanish tagger adapted to Catalan, which is 30.66% above the performance of an unadapted Spanish tagger, and 8.88% below the performance of a supervised tagger trained on annotated Catalan data. Furthermore, we evaluate our model on several Romance, Germanic and Slavic languages and obtain tagging accuracies of up to 92%.

V International Conference on Corpus Linguistics (CILC2013); International audience; The paper presents the early stage of the CRISTAL project, an original French project involving linguists, computer researchers and a firm specializing in multilingual text management. What is at stake from a linguistic point of view is a deeper analysis of the notion of Knowledge Rich Context proposed by Meyer (2001). Using comparable corpora, it analyzes how the notion of KRC can vary according to text genre and/or type of users.

We consider methods for handling incomplete (elliptical) utterances in spoken phraselators, and describe how they have been implemented inside BabelDr, a substantial spoken medical phraselator. The challenge is to extend the phrase matching process so that it is sensitive to preceding dialogue context. We contrast two methods, one using limited-vocabulary strict grammar-based speech and language processing and one using large-vocabulary speech recognition with fuzzy grammar-based processing, and present an initial evaluation on a spoken corpus of 821 context-sentence/elliptical-phrase pairs. The large-vocabulary/fuzzy method strongly outperforms the limited-vocabulary/strict method over the whole corpus, though it is slightly inferior for the subset that is within grammar coverage. We investigate possibilities for combining the two processing paths, using several machine learning frameworks, and demonstrate that hybrid methods strongly outperform the large-vocabulary/fuzzy method.

This paper offers an overview of the history of medial NP-adjuncts from Old English to Present-Day English. In Present-Day English, adverbs are perfectly grammatical in a position between the subject and the main verb ('He recently left for London') whereas NP-adjuncts are at best stylistically marked in this position ('(*)He tomorrow leaves for London'). The paper shows that while medial placement of NP-adjuncts has been considerably less frequent as compared to adverbs ever since around 1500, the contrast was initially much stronger in clauses with finite main verbs than in clauses with finite auxiliaries. It is only in the 19th century that medial placement becomes equally marked in both contexts. These developments are accounted for in terms of processing constraints disfavouring the use of medial NP-adjuncts and a structural reanalysis of NP-medial adjuncts in Late Modern English.

The rapid proliferation of microblogs such as Twitter has resulted in a vast quantity of written text becoming available that contains interesting information for NLP tasks. However, the noise level in tweets is so high that standard NLP tools perform poorly. In this pa- per, we present a statistical truecaser for tweets using a 3-gram language model built with truecased newswire texts and tweets. Our truecasing method shows an improvement in named entity recognition and part-of-speech tagging tasks.

We present an overview of the shared task for spoken CALL. Groups competed on a prompt-response task using English-language data collected, through an online CALL game, from Swiss German teens in their second and third years of learning English. Each item consists of a written German prompt and an audio file containing a spoken response. The task is to accept linguistically correct responses and reject linguistically incorrect ones, with “linguistically correct” being defined by a gold standard derived from human annotations; scoring was performed using a metric defined as the ratio of the relative rejection rates on incorrect and correct responses. The task received twenty entries from nine different groups. We present the task itself, the results, a tentative analysis of what makes items challenging, a comparison between different metrics, and suggestions for a continuation.

This paper reports on challenges and results in developing NLP resources for spoken Rusyn. Being a Slavic minority language, Rusyn does not have any resources to make use of. We propose to build a morphosyntactic dictionary for Rusyn, combining existing resources from the etymologically close Slavic languages Russian, Ukrainian, Slovak, and Polish. We adapt these resources to Rusyn by using vowel-sensitive Levenshtein distance, hand-written language-specific transformation rules, and combinations of the two. Compared to an exact match baseline, we increase the coverage of the resulting morphological dictionary by up to 77.4% relative (42.9% absolute), which results in a tagging recall increased by 11.6% relative (9.1% absolute). Our research confirms and expands the results of previous studies showing the efficiency of using NLP resources from neighboring languages for low-resourced languages. Peer reviewed