Harmonizing Divergent Lemmatization and Part-of-Speech Tagging Practices for L atin Participles through the L i L a Knowledge Base (2025)

Abstract: This paper addresses the challenge of divergent lemmatization and part-of-speech (PoS) tagging practices for Latin participles in annotated corpora. We propose a solution through the LiLa Knowledge Base, a Linked Open Data framework designed to unify lexical and textual data for Latin. Using lemmas as the point of connection between distributed textual and lexical resources, LiLa introduces hypolemmas — secondary citation forms belonging to a word’s inflectional paradigm — as a means of reconciling divergent annotations for participles. Rather than advocating a single uniform annotation scheme, LiLa preserves each resource’s native guidelines while ensuring that users can retrieve and analyze participial data seamlessly. Via empirical assessments of multiple Latin corpora, we show how the LiLa’s integration of lemmas and hypolemmas enables consistent retrieval of participle forms regardless of whether they are categorized as verbal or adjectival.

## introduction lemmatization and part-of-speech (pos) tagging constitute fundamental steps in many natural language processing (nlp) workflows, including information retrieval, machine translation, and sentiment analysis (manning and schutze, 1999; jurafsky and martin, 2025). lemmatization is the process of reducing a word to its canonical form (or lemma), while pos tagging entails assigning discrete grammatical categories (e.g., verb, noun, adjective) to tokens in a text. together, these tasks provide a structured linguistic representation that enables downstream algorithms to handle lexical variation systematically. despite the apparent straightforwardness of these tasks, significant variability arises when moving across different annotation schemes and corpora. one source of variability is the choice of annotation guidelines for morphological categories such as participles. in some corpora, participlesmorphologically derived verb forms that can function as adjectives (e.g., broken window), nouns (e.g., the breaking of the law), or as parts of periphrastic verb tenses (e.g., has broken) -are consistently lemmatized under the corresponding verb root (e.g., break) (see, for latin, busa (1974-1980)). other corpora treat such forms as belonging to the adjective category when they occur in attributive or predicative positions, lemmatizing them separately (e.g., broken) (see, for english, marcus et al. (1993). these divergent lemmatization practices stem from different theoretical perspectives on morphological and syntactic categories, as well as from the practical goals of corpus designers. a similar issue affects pos tagging decisions. for instance, the penn treebank guidelines (marcus et al., 1993) tend to annotate verb-derived adjectives such as broken or burnt as adjectives (with tag: jj) when used attributively (broken glass, burnt toast), whereas the universal dependencies framework (de marneffe et al., 2021) may tag these forms as verb with the accompanying feature for participles (@xmath0, or as adj depending on their syntactic function. these differences can significantly impact the consistency of corpora used in training nlp systems. models trained on one annotation scheme may struggle to generalize effectively to data labeled under a different scheme (atwell et al., 2000). in the context of lemmatization, inconsistent treatment of participles can complicate tasks such as vocabulary alignment and cross-lingual transfer (mcdonald et al., 2011). moreover, variations in lemmatization and pos tagging guidelines impede the comparability of results across distinct corpora, thereby influencing empirical linguistic research. such annotation discrepancies underscore the need for clear and consistent guidelines in lemmatization and pos tagging. nevertheless, accomplishing this task is not straightforward. even within the same language, deciding whether a participial form should be considered purely verbal or adjectival can depend on its syntactic position, degree of lexicalization, and the morphological tradition followed by linguists or corpus designers (aronoff and fudeman, 2022). in highly inflected languages, such as czech, or latin, these decisions become even more complex because participial forms often carry additional morphological information related to gender, number, and case. the ongoing development of universal annotation frameworks like universal dependencies seeks to mitigate some of these inconsistencies by promoting cross-linguistic standards (de marneffe et al., 2021). however, adapting such frameworks to diverse linguistic phenomena remains a non-trivial undertaking, and the tension between theoretical adequacy and practical utility persists. addressing these challenges demands the development and adoption of more harmonized annotation frameworks, to integrate heterogeneous resources while preserving their unique annotation guidelines. in this paper, the divergent criteria employed for lemmatization and pos tagging of participles in multiple latin corpora are empirically examined in a few corpora and a solution to harmonize the divergent annotation practices is proposed. after presenting some issues of divergent lemmatization and pos tagging in latin corpora (section 2), the paper introduces the corpora under consideration as part of the lila knowledge base of interoperable resources for latin (section 3). by exploiting the interoperability among the corpora facilitated by their publication in lila, an empirical assessment is conducted to determine the extent of divergence in lemmatization and pos tagging of participles across the corpora under investigation (section 4). section 5 demonstrates how the modeling based upon an extensive collection of latin lemmas employed by lila enables the harmonization of diverse annotation practices for participles without enforcing a single, uniform approach. finally, section 6 concludes the paper, sketching the future work. ## lemmatization and pos tagging in latin corpora latin, as a highly inflected language, presents numerous challenges for the design and implementation of lemmatization and pos tagging schemes in annotated corpora. available latin resources often diverge in how they treat morphological categories, leading to inconsistencies and reduced interoperability across corpora. a primary source of variation lies in the criteria for determining both the lemma and the pos of morphologically complex forms. like for many other languages, one notable point of discrepancy in latin corpora is the treatment of participles. depending on the corpus or annotation scheme, participles may be categorized as adjectives or verbal forms. in certain corpora, like for instance the index thomisticus corpus (busa, 1974-1980) and treebank (passarotti et al., 2019), participles are mostly lemmatized under their verbal dictionary entry (e.g., laudo for any participial forms of 'to praise'), reflecting the view that participles are primarily verbal derivatives. @xcite conversely, other resources, including the opera latina corpus by lasla (denooz, 2004) and the large repository corpus corporum foot_1 treat participles as distinct lemmas when they exhibit syntactic properties characteristic of adjectives, thereby assigning them an independent lemma (e.g., laudatus -perfect participle of laudo -as a standalone entry when functioning attributively). nonetheless, the boundary between verbal and adjectival functions often remains subtle. these differing conventions can yield inconsistent lexical representations and hamper comparative analyses across datasets. ## the lila knowledge base lila (linking latin) is a linked open data (lod) knowledge base (kb) developed to promote interoperability across a broad spectrum of textual and lexical resources for latin (passarotti et al., 2020). @xcite its conceptual model revolves around two primary components: the lila kb leverages several established ontologies to represent the (meta)data of interlinked linguistic resources. chief among these are powla for corpus data (chiarcos, 2012), olia for linguistic annotation (chiarcos and sukhareva, 2015), and ontolex-lemon for lexical data (mccrae et al., 2017). in addition, lila employs its own ontology foot_5 to model lemmas in the lemma bank as instances of the class lila:lemma, foot_6 defined as a subclass of ontolex:form. @xcite the class lila:lemma has a specific subclass lila:hypolemma, foot_8 whose instances are citation forms that belong to a word's regular inflectional paradigm but receive a different pos tag or degree of comparison than their 'most canonical' lemma, including participles, gerundives, deadjectival adverbs, and comparatives (see section 5). for lexical resources, each lexical entry, modeled using the class ontolex:lexicalentry, foot_9 is connected to its corresponding lemma in the lemma bank through the property ontolex:canonicalform. @xcite with respect to textual resources, tokens are represented as instances of the class terminal foot_11 in the powla ontology and linked to their corresponding lemma in the lemma bank via the property lila:haslemma. @xcite among the textual resources currently interlinked in the lila kb are those examined in this study, selected for their manually verified lemmatization and pos tagging. specifically, they include: ## assessing divergences through lila to investigate lemmatization divergences among the six corpora under examination, we begin by selecting relevant tokens using lila 27 -namely, those linked via the property lila:haslemma to a lemma in the lemma bank with @xmath1. @xcite we then perform minimal preprocessing, removing tokens that are linked to an adj hypolemma but are not participles, specifically gerundives (hypolemmas ending in .*ndus, e.g., laudandus 'to be praised'), and comparatives (hypolemmas ending in .*-or), e.g., citerior 'further' (see section 5). conversely, we retain tokens lemmatized as participles, regardless of their grade or pos features. for instance, we include comparative and superlative forms of both present and perfect participles (e.g., promptiores 'the more attentive (ones)', @xcite abstrusior 'more recondite', @xcite diligentissimo '(to) the most attentive (one)', @xcite desideratissima 'the most desired'), @xcite and adverbs derived from participles (e.g., affluenter 'abundantly', @xcite or fortunate 'fortunately'). @xcite next, tokens are normalized by lowercasing, removing diacritics, and replacing j with i, and v with u. we also remove enclitics by leveraging the lemmatization available in lila; for instance, any @xcite http://lila-erc.eu/data/corpora/classes/id/ corpus 26 http://lila-erc.eu/data/corpora/ corpusfibonacci/id/corpus 27 see the sparql queries (1) and ( 2 ) in the appendix. @xcite the lila lemma bank uses the universal pos tagset (petrov et al., 2011). @xcite lemmatized under promptus ( http://lila-erc.eu/ data/id/hypolemma/35758 ) in the liber abbaci. from these preprocessed items, two lists of normalized types are compiled: (i) types linked to a lemma with @xmath2, and (ii) types linked to a hypolemma with @xmath3. types linked to a verb lemma require further preprocessing, as they may include verb forms that are not participles. to filter out these non-participial forms, these types are processed with the lemlat morphological analyzer for latin (passarotti et al., 2017). only forms recognized as participles are retained, and any remaining homographs (e.g., amatis, which can be either a perfect participle form or the firstperson plural present active indicative of amo 'to love') are resolved through manual verification. for each type, we record the total number of tokens across the six corpora and the distribution within each corpus. these lists are compared to identify shared types, representing participles that exhibit divergent lemmatization strategies in the corpora. an illustrative example is abundans, the present participle of the first-conjugation verb abundo 'to overflow', which appears under the hypolemma abundans (adj) in nine occurrences from the opera latina corpus, and under the lemma abundo (verb) in one occurrence from opera latina, one from the udante treebank, and one from the circse latin library. types linked to an adj hypolemma that do not appear in the verb-linked type list are participles consistently associated with a participle hypolemma across all corpora. conversely, types linked to a verb lemma that do not appear in the adj-linked type list are participles always lemmatized with a verbal lemma. as an initial overview of the data, to provide a more nuanced perspective, focusing on types, for the participle types t that fall under the category verb/adj in and f a (t) are the number of tokens lemmatized as verb or adj respectively for the type t. we estimate an overall index of homogeneity as the average of h(t). h(t) is normalized with values in the range of the interval [0,1], where h(t) = 1 is maximum entropy, i.e., 50% verb and 50% adj, and h(t) = 0 is minimum entropy, i.e., 100% verb and 0% adj, or 0% verb and 100% adj. 36 @xcite since the word types considered are those whose tokens show different pos assignment, maximum and minimum entropy is never found. using the values reported in having established the overall extent of inconsistent pos assignment for participle types across the investigated corpora, tables 3 and 4 present the distribution of participle types, tokens and hapax per corpus according to (in)consistent pos assignment. these tables illustrate the degree of (in)consistency in participle pos assignment within each individual corpus. an examination of the data in tables 3 and 4 indicates that no latin corpus under consideration exhibits completely consistent pos assignment for participle forms. apart from the fibonacci corpus -which, due to its limited size, exerts minimal influence on the overall findings -ittb and circse yield the smallest proportions of participle types that are invariably assigned the adj category. the proportion of participle types that fall within the verb/adj category varies among corpora: it is approximately 2% in ittb, 4% in circse and 8% in lasla. this variability in pos assignment (and by extension, lemmatization) for participles is unsurprising, given the inherently hybrid nature of participles, which can function as both nominal and verbal forms. the universal dependencies documentation about the verbform feature (i.e., form of verb or deverbative) foot_14 states that "some verb forms in some languages actually form a gray zone between category no. types [no. hapax] no. tokens verb only 18,623 [13,497] 105,189 adj only 2,026 [1,320] 8,125 verb/adj 2,202 [0] 41,173 total 22,851 [14,799] 154,487 verb/adj (verb) 23,136 verb/adj (adj) 18,037 to address the challenges of pos assignment for participles in latin corpora, the lila kb has developed a strategy that harmonizes the various criteria followed by these corpora without introducing a new annotation framework. although designed for latin corpora, this solution is languageindependent and can be applied to any language for which a lod collection of lemmas and hypolemmas is made available. ## harmonizing divergences through lila this section describes the methodology used in the lila knowledge base to reconcile discrepancies in the annotation of participles, which may be labeled as either adjectives or verbs in different textual resources. to address this issue, the lemma bank makes use of the class lila:hypolemma, a subclass of lila:lemma (see section 3), to represent citation forms that belong to a word's regular inflectional paradigm but receive a different pos tag or degree of comparison than their 'most canonical' lemma in the lemma bank, hypolemmas are connected to their corresponding lemmas via the symmetric properties lila:hashypolemma 39 and lila:ishypolemma. @xcite for example, the lemma armo 'to furnish with weapons' (verb) 41 is linked via the properties lila:hashypolemma/lila:ishypolemma to three hypolemmas (adj): the participles armans (present tense), armatus (perfect tense), and armaturus (future tense). in the textual resources examined in this study, there are currently 76 occurrences of the different inflected forms of the perfect participle armatus (e.g., armatas, armati, armato) linked to the lemma armo, and 265 occurrences linked to the hypolemma armatus. the modeling approach employed in lila facilitates the reconciliation of these divergent lemmatization practices across multiple corpora by linking the participle forms to the lemma bank. regardless of whether a perfect participle form of armo is treated as an adjective (lemma armatus) or a verb (lemma armo) in individual corpora, its occurrences can be uniformly retrieved and integrated via a sparql query that traverses the lila knowledge graph. this query identifies tokens from different corpora linked, via figure 1 provides a graphical representation of how a textual occurrence of the plural accusative feminine form armatas is linked to the hypolemma armatus, which, in turn, is connected to the lemma armo. this arrangement parallels the linking of future and present participles to the same lemma. the token armatas foot_16 is drawn from vergil's georgica, as indicated in the figure by the link between the token and the document layer of this text via the property powla:haslayer. the lila lemma bank modeling does not include the harmonization of nominalized participle forms with their corresponding base verbs. instead, these forms are recorded as separate lemmas, independent of the verbal lemma from which they originate. for example, in the lemma bank intellectus 'intellect' is listed as a lemma with pos noun, distinct from its base verb intelligo 'to understand'. this decision reflects the fact that fully lexicalized nominalizations typically appear as independent entries in dictionaries and, in most cases, receive pos tag noun in corpus annotation. however, challenges may arise when pos and lemma assignment in a corpus are determined on a contextual basis rather than a strictly lexical one. such challenges occur, for instance, when a participle form is used as a noun in a given context, but this nominalization is not sufficiently lexicalized to warrant its own dictionary entry. in these scenarios, the lila approach typically links such occurrences with their corresponding participle, recorded as a hypolemma with pos adj, rather than creating a distinct lemma for the nominalization in the lemma bank. this is the case of a token like mendicantem 'beggar' (present participle of mendico 'to go begging') in the following sentence drawn from plautus' the captives: ## conclusion this study has highlighted the challenges posed by divergent lemmatization and pos tagging schemes for latin participles in annotated corpora. by demonstrating how these discrepancies can be addressed via the lila knowledge base, we show that heterogeneous annotation practices -whether stemming from theoretical approaches or from the practical aims of corpus designers -hinder interoperability among resources. through lila's lemma bank and the notion of hypolemma, it is possible to unify tokens annotated as either verbal or adjectival participles under a shared representational framework, preserving corpus-specific practices while enabling cross-resource integration. 45 https://lila-erc.eu/data/corpora/lasla/id/ corpus/plautuscaptiui/plautus_captiui_plcapt. bpn_t_0002418 @xcite text and translation of this excerpt are drawn from de melo (2011). rather than enforcing a single "correct" solution, lila's graph-based design allows researchers to explore and compare multiple annotation strategies across corpora with minimal manual intervention. in so doing, it promotes data interoperability, and provides a robust platform for linguistic research and nlp applications. ultimately, this approach underscores the value of lod methodologies in bridging divergent annotation practices and advancing the broader goal of accessible and reusable linguistic resources. in future research, we aim to extend our analysis to include nominalized participle forms, which may be documented as independent entries and lemmas in both lexical and textual resources, as well as in the lemma bank. after collecting the set of nominalized participle tokens from corpora and corresponding entries from the lexical resources published in lila, we will apply the same analytical methodology outlined in this study. this will allow us to assess the degree of consistency in the treatment of nominalized participles across different linguistic resources. finally, given the language-independent nature of lila's strategy for harmonizing pos assignment divergences in participles, we hope that other languages will adopt the same architecture. in particular, building and publishing collections of lemmas and hypolemmas as lod for different languages is crucial for enabling distributed linguistic resources to interoperate in the semantic web. a pertinent example is offered by the liita knowledge base, which has recently implemented a lemma bank to enhance lod-based interoperability across italian linguistic resources (litta et al., 2024). @xcite