A Comparative Study of Static and Contextual Embeddings for Analyzing Semantic Changes in Medieval L atin Charters (2025)

Abstract: The Norman Conquest of 1066 C.E. brought profound transformations to England’s administrative, societal, and linguistic practices. The DEEDS (Documents of Early England Data Set) database offers a unique opportunity to explore these changes by examining shifts in word meanings within a vast collection of Medieval Latin charters. While computational linguistics typically relies on vector representations of words like static and contextual embeddings to analyze semantic changes, existing embeddings for scarce and historical Medieval Latin are limited and may not be well-suited for this task. This paper presents the first computational analysis of semantic change pre- and post-Norman Conquest and the first systematic comparison of static and contextual embeddings in a scarce historical data set. Our findings confirm that, consistent with existing studies, contextual embeddings outperform static word embeddings in capturing semantic change within a scarce historical corpus.

## introduction the norman conquest of 1066 is a pivotal event in english history, marked by the introduction of new administrative and cultural practices by the normans. this transformation is evident in the medieval latin charters -official documents recording legal agreements, grants, rights, and privileges -preserved in the deeds (documents of early england data set) corpus @xcite . one implication of these transformations is the shift in language usage and word meanings within the medieval latin charters, illustrated by the following examples: comes generally meant "official" in anglo-saxon charters, but in norman documents, it consistently appeared as a title meaning "earl" or "count"; proprius ("one's own") was used by the anglo-saxons to indicate signing a document * corresponding author "with one's own hand," whereas the normans used it to refer to property ownership. investigating these changes in word meanings before and after the norman conquest -a process known as lexical semantic change (lsc) -provides insights into the cultural and societal transformations while also posing challenging research questions on how to systematically model this change. in the field of computational linguistics, various methods have been proposed for modeling lexical semantics and thereby for studying semantic changes. in earlier years, static word embedding approaches, where each word was mapped to a fixed vector representation based on its co-occurrence patterns with other words within a corpus @xcite , were dominant and proven effective in lsc studies @xcite . in more recent years, contextual representations, which provide different vectors for the different contexts in which a word appears @xcite , have achieved state-of-the-art performance in lsc studies, likely due to their ability to handle phenomena like polysemy and homonymy more effectively than static representations @xcite @xcite . despite the successes of contextual embeddings in lsc research, they are typically trained on large corpora @xcite and require significantly more training data than static embeddings due to their more complex architectures and larger parameter sizes @xcite . this poses a challenge for studies involving smaller data sets such as the deeds medieval latin corpus, which contains only 17k charters and 3m tokens -considerably smaller than the billiontoken corpora typically used to train contextual embeddings @xcite . meanwhile, the medieval latin charters contain a rich and expansive vocabulary, including local dialects and borrowings from other languages (e.g., the anglo-saxon manuscripts include an extensive amount of old english). these factors collectively raise concerns about the adaptability and relative performance of existing embedding methods in this scarce and heteroglossic data set. therefore, this paper aims to address the research gap in medieval latin charters with the following contributions: the rest of this paper is organized as follows. section 2 summarizes the previous literature on static and contextual embeddings. section 3 provides a detailed introduction to the deeds data set. section 4 outlines the training process for the different embedding methods on this corpus. foot_0 sections 5 and 6 present the experiments, results, and discussions related to evaluating these embedding methods in capturing semantic change. ## related work the standard computational approach for lexical semantic change (lsc) analysis involves separately training embeddings for different periods within a corpus @xcite , and then measuring the distance between the representations of a given word across these periods. in this section, we review the current approaches of semantic change analysis using static and contextual embeddings and their applications to medieval latin corpora. ## data for our analysis, we used medieval latin charters from deeds (documents of early england data set). 3 the deeds database contains transcripts of over 70k latin charters from the 7th to the 14th century. of these, 40k pertain to england, and 17k are dated. they are official documents issued by kings and commoners and deal with the transfer of property and property rights. in this study, we focused on the 17k dated charters, as the dates were essential for splitting the corpus for semantic change analysis. we split the corpus into three sets: the anglo-saxon period (from 589 to 1066 ce), referred to as ang in later sections; the norman period (from 1066 to 1153 ce), referred to as nor; the later post-conquest period up to 1272 ce (also called plantagenet period), referred to as pla. the main focus of this paper is the semantic change induced by the norman conquest (i.e., the transition from ang to nor periods, referred to as an in the later section). for comparison, we also examine the transitions from nor to pla, referred to as np. ## lexical similarity analysis 5.1 similarity measures to evaluate the applicability of different embedding models in analyzing semantic change within the medieval latin charters, we conducted a semantic similarity analysis across various periods following the approach of @xcite . specifically, for a given word w occurring in two periods t 1 and t 2 , we computed the cosine similarity between their embeddings w t 1 and w t 2 using the following formula: a lower cosine similarity score between periods suggests a potential semantic shift in the word's meaning @xcite . in our analysis, we divided the data into three periods, as outlined in section 3, and therefore, for each word, we computed two cosine similarity measures: cos an , representing the transition from ang to nor and cos n p , representing the transition from nor to pla. we will refer to the above labels in later sections. ## conclusion this paper represents the first effort to explore semantic changes in the medieval latin charters as a result of the norman conquest, and the first to systematically implement and compare static and contextual word embeddings in the context of the scarce and historical corpus. our evaluation on the deeds medieval latin charters corpus with manually labeled semantic changes demonstrates that contextual embeddings outperform static word embeddings, even on a scarce and complex historical data set. this finding is consistent with results from large contemporary data sets and confirms the adaptability of contextual embeddings to smaller data sets beyond what has been shown in existing literature. furthermore, consistent with previous work on building contextual embeddings for historical corpora @xcite , training from scratch yields better performance in capturing the correlation between semantic change labels and similarity measures.