<h4>Objective</h4>Ontologies are essential for representing the knowledge of a domain. To make ontologies useful, they must encompass a comprehensive domain view. To achieve ontology enrichment, there is a need to discover new concepts to be added, either because they were missed in the first place, or the state-of-the-art has advanced to develop new real-world concepts. Our goal is to develop an automatic enrichment pipeline using a seed ontology, a Large Language Model (LLM), and source of text. The pipeline is applied to the domain of Social Determinants of Health (SDoH), using PubMed as a source of concepts. In this work, the applicability and effectiveness of the enrichment pipeline is demonstrated by extending the SDoH Ontology called SOHOv1, however our methodology could be used in other domains as well.<h4>Methods</h4>We first retrieved PubMed abstracts of candidate articles with existing SOHOv1 concepts as search terms. Next, we used GPT-4-1201 to extract semantic triples from the abstracts. We identified concepts from these triples utilizing lexical, semantic, and knowledge network-based filtering. We also compared the granularity of semantic triples extracted with our method to the triples in the SemMedDB (Semantic MEDLINE Database). The results were evaluated by human experts and standard ontology tools for checking consistency and semantic correctness.<h4>Results</h4>We expanded SOHOv1, which contained 173 concepts and 585 axioms, including 207 logical axioms to SOHOv2, which contains 572 concepts, 1,542 axioms, including 725 logical axioms. Our methods identified more concepts than those extracted from SemMedDB for the same task. While we have shown the feasibility of our approach for an SDoH ontology, the methodology is generalizable to other ontologies with an existing seed ontology and text corpus.<h4>Conclusions</h4>The contributions of this work are: Extracting semantic triples from PubMed abstracts using GPT-4-1201 utilizing prompt chaining; showing the superiority of triples from GPT-4-1201 over triples from SemMedDB for SDoH; using lexical and semantic similarity search techniques with knowledge network-based search to identify the concepts to be added to the ontology; confirming the quality of the new concepts with human experts.

ontology to represent and classify objects. They develop conceptual frameworks, called ontologies, for limited domains, such as a database with categories like Metaphysics is the branch of philosophy that examines the basic nature or most fundamental structure of reality. It is traditionally seen as the study of mind-independent features of the world, but some theorists view it as an inquiry into the conceptual framework of human understanding. Some philosophers, including Aristotle, designate metaphysics as the first philosophy to suggest that it is mor Metaphysicians often regard existence or being as one of the most basic and general concepts. To exist means to be part of reality, distinguishing real entities from imaginary ones. According to a traditionally influential view, existence is a property of properties: if an entity exists then its properties are instantiated. A different position states that existence is a property of individuals, meaning that it is similar to other properties, such as shape or size. It is… Computer scientists rely on metaphysics in the form of ontology to represent and classify objects. They develop conceptual frameworks, called ontologies, for limited domains, such as a database with categories like person, company, address, and name to represent information about clients and employees. Ontologies provide standards for encoding and storing information in a structured way, allowing computational processes to use the information for various purposes. Upper ontologies, such as Suggested Upper Merged Ontology and Basic Formal Ontology, define concepts at a more abstract level, making it possible to integrate information belonging to different domains. Logic as the study of correct reasoning is often used by metaphysicians to engage in their inquiry and express insights through precise logical formulas. Another relation between the two fields concerns the metaphysical assumptions associated with logical systems. Many logical systems l Metaphysics is the branch of philosophy that examines the basic nature or most fundamental structure of reality. It is traditionally seen as the study of mind-independent features of the world, but some theorists view it as an inquiry into the conceptual framework of human understanding. Some philosophers, including Aristotle, designate metaphysics as the first philosophy to suggest that it is more fundamental than other forms of philosophical inquiry. Metaphysics encompasses a wide range of general and abstract topics. It investigates the nature of existence, the features all entities have in common, and their division into categories of being. Some definitions are descriptive by providing an account of what metaphysicians do while others are normative and prescribe what metaphysicians ought to do. Two historically influential definitions in ancient and medieval philosophy understand metaphysics as the science of the first causes and as the study of being qua being, that is, the topic of what all beings have in common and to what fundamental categories they belong. In the modern period, the scope of metaphysics has expanded to include topics such as the distinction between mind and body and free will. For instance, Plato held that Platonic forms, which are perfect and immutable ideas, have a higher degree of existence than matter, which can only imperfectly reflect Platonic forms. Another key concern in metaphysics is the division of entities into distinct groups based on underlying features they share. Theories of categories provide a system of the most fundamental kinds or the highest genera of being by establishing a comprehensive inventory of everything. One of the earliest theories of categories was proposed by Aristotle, who outlined a system of 10 categories. According to a common view, concrete objects, like rocks, trees, and human beings, exist in space and time, undergo changes, and impact each other as cause and effect. They contrast with abstract objects, like numbers and sets, which do not exist in space and time, are immutable, and do not engage in causal relations. === Particulars === Particulars are individual entities and include both concrete objects, like Aristotle, the Eiffel Tower, or a specific apple, and abstract objects, like the number 2 or a specific set in mathematics. According to this view, the disagreement in the metaphysics of composition about whether there are tables or only particles arranged table-wise is a trivial debate about linguistic preferences without any substantive consequences for the nature of reality. The position that metaphysical disputes have no meaning or no significant point is called metaphysical or ontological deflationism. This view is opposed by so-called serious metaphysicians, who contend that metaphysical disputes are about substantial features of the underlying structure of reality. Key differences are that metaphysics relies on rational inquiry while physical cosmology gives more weight to empirical observations and theology incorporates divine revelation and other faith-based doctrines. Historically, cosmology and theology were considered subfields of metaphysics. Computer scientists rely on metaphysics in the form of ontology to represent and classify objects. They develop conceptual frameworks, called ontologies, for limited domains, such as a database with categories like person, company, address, and name to represent information about clients and employees. He also proposed a system of categories and developed a comprehensive framework of the natural world through his theory of the four causes. Starting in the 4th century BCE, Hellenistic philosophy explored the rational order underlying the cosmos and the laws governing it. Neoplatonism emerged towards the end of the ancient period in the 3rd century CE and introduced the idea of "the One" as the transcendent and ineffable source of all creation. Meanwhile, in Indian Buddhism, the Madhyamaka school

Semantic verbal fluency tasks (SFT) provide a window into the structure and dynamics of the mental lexicon by eliciting word sequences guided primarily by semantic associations. We propose a probabilistic framework that models SFT as censored random walks on semantic networks, extended with pseudo-nodes to account for local and global jumps. This representation enables the integration of associative retrieval and sudden resets, capturing both clustering and switching processes. To assess model quality, we define a suite of complementary metrics-global likelihood, frequency likelihood, and bigram relevance-that evaluate not only overall fit but also the distributional properties of word associations. Using a dataset of 677 lists in the category "clothing," we benchmark existing techniques against our proposed BIGRAM-CN model, which combines statistical constraints with empirical frequencies of word-to-word transitions. Results show that BIGRAM-CN avoids overfitting, generalizes across training and test data, and synthesizes realistic lists more accurately than prior approaches. This work advances computational models of lexical retrieval and offers practical tools for comparing populations, categories, and cognitive profiles in both linguistic and psychological research. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . Semantic verbal fluency tasks (SFT) provide a window into the structure and dynamics of the mental lexicon by eliciting word sequences guided primarily by semantic associations. Studying the conceptual structure of a language offers insight into how the mind organizes our perception of reality. The information that shapes the meaning of linguistic units derives not only from our interaction with the environment, but also from the linguistic context in which these words are used. All this lexical-semantic knowledge has been studied through the theoretical construct of the mental lexicon (Pirrelli et al., 2020 ). Conceived as a dynamic cognitive system that integrates word forms, meanings, and their interrelationships, it underlies both conscious and unconscious lexical activity (Jarema & Libben, 2007 ). One enduring and influential perspective on the architecture and dynamics of the mental lexicon conceptualizes it as a metaphorical network, in which each word is represented as a node and the relationships between words as connecting edges (Aitchison, 2008 ; Meara, 2009 ). This view aligns with early network activation theories, according to which word retrieval is driven by the spread of activation from a cue toward semantically connected concepts (Collins & Loftus, 1975 ). In contrast, spatial models posit that words occupy positions within a multidimensional semantic space, where distances correspond to degrees of similarity. Participants were allotted 2 min to generate responses for each category. All responses were subsequently transcribed into a digital database and systematically reviewed to eliminate errors and duplicate entries. Inflectional variants of the same lexical item were standardized under a single lemma (camisa and camisas in camisa/s “shirt/s”). Forms in which variation in gender or number entailed a semantic or conceptual distinction were treated as separate entries (gorro “hat” and gorra “cap”). The proposed criteria aim to answer the following questions: Which words? The number of words is not the only meaningful indicator, as the specific words included in the list also convey important information. Examining whether an individual, a group, or a model tends to produce overly rare or overly common words can provide insight into their lexical access and cognitive strategy. How do the words associate among them? The order in which words are In the absence of a standardized taxonomy for the clothing category in Spanish, we generated a classification using a large language model (LLM), later supervised by the research team. Each word was assigned to one or more semantic categories (e.g., anatomical location, context of use, or material). A transition was identified as a “jump” if the two words shared no common categories. While this definition is conservative and tends to reduce the absolute number of identified switches, it establishes a robust and reasonable framework for evaluating the predictive capacity of our model's indicators. In this context, we analyzed two local topological metrics: node degree and semantic cohesion. Second, once the model’s quality is established, these measures allow for the identification of differences between models fitted to different groups (e.g., male/female, children/adults, native/non-native speakers, clinical/nonclinical populations), across various semantic categories (natural categories, ad hoc categories, schemas, etc.), and along different dimensions (e.g., overall likelihood, list length, word frequency, and associative structure). The frequency likelihood metric shows that only the BIGRAM-CN model with γ =1.10 generates lists with a word frequency distribution truly comparable to that of the original data. The bigram metric shows that both BIGRAM-CN and INVITE-CN produce a distribution of relevant bigrams equivalent to that of the training data. We can therefore conclude that the BIGRAM-CN model generation technique provides the best overall fit across all metrics and is particularly suitable for synthesizing lists similar to those observed in training. Conclusions The SFT is a well-established procedure used in linguistics to identify the underlying semantic network.

like the number 7. Systems of categories aim to provide a comprehensive inventory of reality by employing categories such as substance, property, relation Ontology is the philosophical study of being. It is traditionally understood as the subdiscipline of metaphysics focused on the most general features of reality. As one of the most fundamental concepts, being encompasses all of reality and every entity within it. To articulate the basic structure of being, ontology examines the shared characteristics among all things and investigates their classif On…

world, the mental world, and the social world) words and phrases are organized by semantic categories and subcateogies (see the list on pp. xxix–xxx of