Papers by Gülşen Eryiğit
Towards Automatic Grammatical Error Type Classification for Turkish (2023.eacl-srw)
Copied to clipboard
| Challenge: | Existing error types are not universal, resulting in many language specific variants. |
| Approach: | They propose to use a rule-based error type classification pipeline to classify edits into predefined error categories for Turkish . they propose to change existing error categories to suit the inflectional and derivational properties of the language . |
| Outcome: | The proposed system is evaluated on 106 annotated sentences and its performance is measured as 77.04% F0.5 score. |
Extracting Complex Relations from Banking Documents (D19-51)
Copied to clipboard
| Challenge: | Existing methods to extract complex relations from banking orders are limited . formal letters, petitions, demands or complaints are still a major communication medium in corporate banking. |
| Approach: | They propose a relation extraction method that extracts intersentential, nested and complex relations from banking orders. |
| Outcome: | The proposed method shows 11% error reduction over previous methods. |
Typology-Aware Multilingual Morphosyntactic Parsing with Joint Abstract Node Modeling (2026.acl-long)
Copied to clipboard
| Challenge: | UniDive 2025 Morphosyntactic Parsing (MSP) shared task unifies dependency structure, morphological features, and unrealized arguments. |
| Approach: | They propose a multilingual, typology-aware joint system that integrates word-type prediction, content-only parsing, morphological tagging, and an abstract-node component within a single architecture. |
| Outcome: | The proposed model outperforms the leading submission by 3.23 percentage points in MSLAS, 3.35 in LAS, and 1.78 in FEATS macro F1. |
CorefInst: Leveraging LLMs for Multilingual Coreference Resolution (2026.tacl-1)
Copied to clipboard
| Challenge: | Existing methods for CR are encoder-only, decoder-based and asynchronous models. |
| Approach: | They propose a multilingual CR methodology which leverages decoder-only LLMs to handle overt and zero mentions. |
| Outcome: | The proposed model outperforms the leading multilingual CR model by 2 percentage points across all languages in the CorefUD v1.2 dataset. |
Constructing Multimodal Language Learner Texts Using LARA: Experiences with Nine Languages (2020.lrec-1)
Copied to clipboard
Elham Akhlaghi, Branislav Bédi, Fatih Bektaş, Harald Berthelsen, Matthias Butterweck, Cathy Chua, Catia Cucchiarin, Gülşen Eryiğit, Johanna Gerlach, Hanieh Habibi, Neasa Ní Chiaráin, Manny Rayner, Steinþór Steingrímsson, Helmer Strik
| Challenge: | LARA is an open source project that aims to support easy conversion of plain texts into online versions suitable for use by language learners. |
| Approach: | They propose to support easy conversion of plain texts into online versions suitable for use by language learners. |
| Outcome: | The proposed platform is suitable for creating texts in multiple languages via crowdsourcing techniques that can be used for teaching a language via reading and listening. |
AMR Alignment for Morphologically-rich and Pro-drop Languages (2022.acl-srw)
Copied to clipboard
| Challenge: | Existing AMR aligners for English are not well suited for many languages where many concepts appear from morphologically-semantic elements. |
| Approach: | They propose to use a tree traversal approach to align AMR concepts from morphemes in a Turkish language. |
| Outcome: | The proposed aligner outperforms the existing aligners for English and Portuguese in terms of precision, recall and F1 score. |
Incorporating Dropped Pronouns into Coreference Resolution: The case for Turkish (2023.eacl-srw)
Copied to clipboard
| Challenge: | PD-MRLs are pro-drop and morphologically rich languages due to dropped pronouns . a representation & evaluation scheme is proposed to incorporate dropped pronomins into coreference resolution . |
| Approach: | They propose a representation & evaluation scheme to incorporate dropped pronouns into coreference resolution and validate it on the Turkish language. |
| Outcome: | The proposed representation & evaluation scheme extends on the Turkish coreference dataset . it includes pre and post processors to enhance the prominent CoNLL coreference scorer . |
Towards Turkish Abstract Meaning Representation (P19-2)
Copied to clipboard
| 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. |