Search Results for author: Sarah Moeller

Found 12 papers, 0 papers with code

IGT2P: From Interlinear Glossed Texts to Paradigms

no code implementations EMNLP 2020 Sarah Moeller, Ling Liu, Changbing Yang, Katharina Kann, Mans Hulden

An intermediate step in the linguistic analysis of an under-documented language is to find and organize inflected forms that are attested in natural speech.

POS

Disambiguation of morpho-syntactic features of African American English – the case of habitual be

no code implementations LTEDI (ACL) 2022 Harrison Santiago, Joshua Martin, Sarah Moeller, Kevin Tang

To overcome the scarcity, we employ a combination of rule-based filters and data augmentation that generate a corpus balanced between habitual and non-habitual instances.

Data Augmentation

Disambiguation of morpho-syntactic features of African American English -- the case of habitual be

no code implementations26 Apr 2022 Harrison Santiago, Joshua Martin, Sarah Moeller, Kevin Tang

To overcome the scarcity, we employ a combination of rule-based filters and data augmentation that generate a corpus balanced between habitual and non-habitual instances.

Data Augmentation

To POS Tag or Not to POS Tag: The Impact of POS Tags on Morphological Learning in Low-Resource Settings

no code implementations ACL 2021 Sarah Moeller, Ling Liu, Mans Hulden

However, the importance and usefulness of POS tags needs to be examined as NLP expands to low-resource languages because linguists who provide many annotated resources do not place priority on early identification and tagging of POS.

POS TAG

The Russian PropBank

no code implementations LREC 2020 Sarah Moeller, Irina Wagner, Martha Palmer, Kathryn Conger, Skatje Myers

This paper presents a proposition bank for Russian (RuPB), a resource for semantic role labeling (SRL).

Frame Semantic Role Labeling

Linguistic Analysis Improves Neural Metaphor Detection

no code implementations CONLL 2019 Kevin Stowe, Sarah Moeller, Laura Michaelis, Martha Palmer

In the field of metaphor detection, deep learning systems are the ubiquitous and achieve strong performance on many tasks.

Automatic Glossing in a Low-Resource Setting for Language Documentation

no code implementations COLING 2018 Sarah Moeller, Mans Hulden

Morphological analysis of morphologically rich and low-resource languages is important to both descriptive linguistics and natural language processing.

Morphological Analysis

A Neural Morphological Analyzer for Arapaho Verbs Learned from a Finite State Transducer

no code implementations COLING 2018 Sarah Moeller, Ghazaleh Kazeminejad, Andrew Cowell, Mans Hulden

We experiment with training an encoder-decoder neural model for mimicking the behavior of an existing hand-written finite-state morphological grammar for Arapaho verbs, a polysynthetic language with a highly complex verbal inflection system.

Machine Translation Morphological Analysis +1

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