# LSCDiscovery: A shared task on semantic change discovery and detection in Spanish

arXiv: https://arxiv.org/abs/2205.06691 · HTML: https://mlsanity.com/paper/2205.06691/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- Builds on 25 of its 52 references that are in the map.
- First posted on arXiv 13 May 2022.

## Builds on (most cited first, 25 of 25)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Efficient Estimation of Word Representations in Vector Space](https://mlsanity.com/paper/1301.3781/) (2013)
- [Unsupervised Cross-lingual Representation Learning at Scale](https://mlsanity.com/paper/1911.02116/) (2019)
- [Distributed Representations of Words and Phrases and their Compositionality](https://mlsanity.com/paper/1310.4546/) (2013)
- [SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection](https://mlsanity.com/paper/2007.11464/) (2020)
- [Diachronic word embeddings and semantic shifts: a survey](https://mlsanity.com/paper/1806.03537/) (2018)
- [Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Change](https://mlsanity.com/paper/1606.02821/) (2016)
- [Survey of Computational Approaches to Lexical Semantic Change](https://mlsanity.com/paper/1811.06278/) (2018)
- [Diachronic Usage Relatedness (DURel): A Framework for the Annotation of Lexical Semantic Change](https://mlsanity.com/paper/1804.06517/) (2018)
- [Explaining and Improving BERT Performance on Lexical Semantic Change Detection](https://mlsanity.com/paper/2103.07259/) (2021)
- [UiO-UvA at SemEval-2020 Task 1: Contextualised Embeddings for Lexical Semantic Change Detection](https://mlsanity.com/paper/2005.00050/) (2020)
- [A Wind of Change: Detecting and Evaluating Lexical Semantic Change across Times and Domains](https://mlsanity.com/paper/1906.02979/) (2019)
- [DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languages](https://mlsanity.com/paper/2104.08540/) (2021)
- [RuSemShift: a dataset of historical lexical semantic change in Russian](https://mlsanity.com/paper/2010.06436/) (2020)
- [Challenges for Computational Lexical Semantic Change](https://mlsanity.com/paper/2101.07668/) (2021)
- [Dialectometric analysis of language variation in Twitter](https://mlsanity.com/paper/1702.06777/) (2017)
- [Lexical Semantic Change Discovery](https://mlsanity.com/paper/2106.03111/) (2021)
- [Grammatical Profiling for Semantic Change Detection](https://mlsanity.com/paper/2109.10397/) (2021)
- [CIRCE at SemEval-2020 Task 1: Ensembling Context-Free and Context-Dependent Word Representations](https://mlsanity.com/paper/2005.06602/) (2020)
- [Uncovering divergent linguistic information in word embeddings with lessons for intrinsic and extrinsic evaluation](https://mlsanity.com/paper/1809.02094/) (2018)
- [UWB at SemEval-2020 Task 1: Lexical Semantic Change Detection](https://mlsanity.com/paper/2012.00004/) (2020)
- [Simulating Lexical Semantic Change from Sense-Annotated Data](https://mlsanity.com/paper/2001.03216/) (2020)
- [IMS at SemEval-2020 Task 1: How low can you go? Dimensionality in Lexical Semantic Change Detection](https://mlsanity.com/paper/2008.03164/) (2020)
- [OP-IMS @ DIACR-Ita: Back to the Roots: SGNS+OP+CD still rocks Semantic Change Detection](https://mlsanity.com/paper/2011.03258/) (2020)
- [Shared task: Lexical semantic change detection in German (Student Project Report)](https://mlsanity.com/paper/2001.07786/) (2020)

## Built on by (most cited first, 11 of 11)

- [A Survey on Contextualised Semantic Shift Detection](https://mlsanity.com/paper/2304.01666/) (2023)
- [Machine-assisted quantitizing designs: augmenting humanities and social sciences with artificial intelligence](https://mlsanity.com/paper/2309.14379/) (2023)
- [Substitution-based Semantic Change Detection using Contextual Embeddings](https://mlsanity.com/paper/2309.02403/) (2023)
- [The LSCD Benchmark: a Testbed for Diachronic Word Meaning Tasks](https://mlsanity.com/paper/2404.00176/) (2024)
- [Presence or Absence: Are Unknown Word Usages in Dictionaries?](https://mlsanity.com/paper/2406.00656/) (2024)
- [BOS at LSCDiscovery: Lexical Substitution for Interpretable Lexical Semantic Change Detection](https://mlsanity.com/paper/2206.11865/) (2022)
- [Computational modeling of semantic change](https://mlsanity.com/paper/2304.06337/) (2023)
- [Tracking Semantic Change in Slovene: A Novel Dataset and Optimal Transport-Based Distance](https://mlsanity.com/paper/2402.16596/) (2024)
- [Evaluating the Evaluator: Problems with SemEval-2020 Task 1 for Lexical Semantic Change Detection](https://mlsanity.com/paper/2604.13232/) (2026)
- [A Tale of Two Laws of Semantic Change: Predicting Synonym Changes with Distributional Semantic Models](https://mlsanity.com/paper/2305.19143/) (2023)
- [CALE : Concept-Aligned Embeddings for Both Within-Lemma and Inter-Lemma Sense Differentiation](https://mlsanity.com/paper/2508.04494/) (2025)

## Abstract (arXiv)

We present the first shared task on semantic change discovery and detection in Spanish and create the first dataset of Spanish words manually annotated for semantic change using the DURel framework (Schlechtweg et al., 2018). The task is divided in two phases: 1) Graded Change Discovery, and 2) Binary Change Detection. In addition to introducing a new language the main novelty with respect to the previous tasks consists in predicting and evaluating changes for all vocabulary words in the corpus. Six teams participated in phase 1 and seven teams in phase 2 of the shared task, and the best system obtained a Spearman rank correlation of 0.735 for phase 1 and an F1 score of 0.716 for phase 2. We describe the systems developed by the competing teams, highlighting the techniques that were particularly useful and discuss the limits of these approaches.