| Challenge: | Abstract Meaning Representation (AMR) is a recent and prominent meaning representation with good acceptance and several applications in the Natural Language Processing area. |
| Approach: | They propose to build an AMR annotated corpus for Brazilian Portuguese using an alignment-based approach. |
| Outcome: | The proposed corpus is based on the Little Prince book, which went into the public domain and explored some language-specific annotation issues. |
Similar Papers
Semantically Inspired AMR Alignment for the Portuguese Language (2020.emnlp-main)
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| Challenge: | Abstract Meaning Representation (AMR) parsers require alignment between nodes and words of the sentence. |
| Approach: | They propose to use a more semantically matched word-concept pair to align graphs with words in Portuguese . they performed intrinsic and extrinsic evaluations and found it outperforms the English alignment strategies. |
| Outcome: | The proposed method outperforms the existing methods for English and achieves competitive results with a parser designed for the Portuguese language. |
The New Propbank: Aligning Propbank with AMR through POS Unification (L18-1)
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| Challenge: | Existing Propbank corpus converts sense labels to a format which is more compatible with AMR and more robust to sparsity. |
| Approach: | They propose a corpus which converts existing Propbank sense labels to a new unified format which is more compatible with AMR and more robust to sparsity. |
| Outcome: | The proposed format is more compatible with AMR and robust to sparsity. |
AMR Beyond the Sentence: the Multi-sentence AMR corpus (C18-1)
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| Challenge: | Abstract Meaning Representation (AMR) is limited to capturing the semantics of individual sentences. |
| Approach: | They propose a corpus that annotates coreference and similar phenomena on top of existing AMRs. |
| Outcome: | The proposed corpus is compared with existing corpora on sentence-level semantics . it shows that it can be used for information extraction and question answering . |
Natural Language Generation: Recently Learned Lessons, Directions for Semantic Representation-based Approaches, and the Case of Brazilian Portuguese Language (P19-2)
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| Challenge: | Natural Language Generation (NLG) is a promising area in Natural Language Processing (NLP) . |
| Approach: | They present a review of the literature on Natural Language Generation in Brazilian Portuguese. |
| Outcome: | The proposed approaches are based on the Abstract Meaning Representation formalism and have potential future directions. |
Towards Turkish Abstract Meaning Representation (P19-2)
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| Challenge: | Abstract Meaning Representation (AMR) abstracts away from syntactic features such as word order and does not annotate every constituent in a sentence. |
| Approach: | They have built a first Turkish AMR corpus by hand-annotating 100 sentences from the novel "The Little Prince" they will use the results to prepare a Turkish AML annotation specification for future annotators. |
| Outcome: | The results of the study compare Turkish AMRs with English AMR annotations . the proposed framework is expected to be used in training future annotators. |
Annotating Abstract Meaning Representations for Spanish (L18-1)
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| Challenge: | Abstract Meaning Representation (AMR) is a semantic representation language for natural language processing. |
| Approach: | They propose a method that would lay the groundwork for building a large semantic bank for Spanish . they propose to use a database to annotate AMRs for other languages . |
| Outcome: | The proposed method would lay the groundwork for building a large semantic bank for Spanish and guide those who would like to implement it for other languages. |
Building The First English-Brazilian Portuguese Corpus for Automatic Post-Editing (2020.coling-main)
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| Challenge: | Existing corpus for automatic post-editing of English and Brazilian Portuguese is limited. |
| Approach: | They introduce a corpus for Automatic Post-Editing of English and Brazilian Portuguese. |
| Outcome: | The proposed corpus improves on the English and Brazilian Portuguese languages. |
A Corpus of German Abstract Meaning Representation (DeAMR) (2024.lrec-main)
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| Challenge: | Abstract Meaning Representations (AMRs) are semantic graphs that abstract away from surface syntax and capture the meaning of who does what to whom in a sentence. |
| Approach: | They propose to use German Abstract Meaning Representation (Deutsche AMR) to represent the structure and semantics of German. |
| Outcome: | The proposed framework is based on an annotated corpus of 400 DeAMR in German and is validated through inter-annotator agreement. |
Back-Translation as Strategy to Tackle the Lack of Corpus in Natural Language Generation from Semantic Representations (D19-63)
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| Challenge: | Abstract Meaning Representation and Brazilian Portuguese (BP) are selected as semantic representation and language, respectively. |
| Approach: | They propose to use Brazilian Portuguese and Abstract Meaning Representation as semantic representations for NLG. |
| Outcome: | The proposed methods were evaluated on two datasets (one automatically generated and another human-generated) to compare the performance in a real context. |
The brWaC Corpus: A New Open Resource for Brazilian Portuguese (L18-1)
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| Challenge: | a large corpus for Brazilian Portuguese is needed for NLP applications . the corpus is 2.7 billion tokens, and domain diversity is maximized . |
| Approach: | They propose to build a large Web corpus for Brazilian Portuguese with 2.7 billion tokens . they also propose an updated sentence-level approach for the strict removal of duplicated content . |
| Outcome: | The proposed corpus is based on a pipeline methodology and is available for querying and downloading. |