TiFi: Taxonomy Induction for Fictional Domains [Extended version]

Taxonomies are important building blocks of structured knowledge bases, and their construction from text sources and Wikipedia has received much attention. In this paper we focus on the construction of taxonomies for fictional domains, using noisy category systems from fan wikis or text extraction as input. Such fictional domains are archetypes of entity universes that are poorly covered by Wikipedia, such as also enterprise-specific knowledge bases or highly specialized verticals. Our fiction-targeted approach, called TiFi, consists of three phases: (i) category cleaning, by identifying candidate categories that truly represent classes in the domain of interest, (ii) edge cleaning, by selecting subcategory relationships that correspond to class subsumption, and (iii) top-level construction, by mapping classes onto a subset of high-level WordNet categories. A comprehensive evaluation shows that TiFi is able to construct taxonomies for a diverse range of fictional domains such as Lord of the Rings, The Simpsons or Greek Mythology with very high precision and that it outperforms state-of-the-art baselines for taxonomy induction by a substantial margin

Antecedentem creavit consequens: Friedrich Schlegel’s ontology of time and literary forms in Rede an die Mytologie

We attempt to offer a new interpretation of Schlegel’s original solution for the problem of the new mythology. We claim that, while grasping the problem of the missing center as the structure of modern thought, Schlegel develops a theory of literature which implies an ontology of time. We advance that, by identifying myth with romantic literature, Schlegel’s argumentative economy leads him to apply the metaphysical predicates of myth to romantic literature as such. We propose then to read the status of literary forms as constituting the substance which precedes them but, paradoxically, only exists through them.We attempt to offer a new interpretation of Schlegel’s original solution for the problem of the new mythology. We claim that, while grasping the problem of the missing center as the structure of modern thought, Schlegel develops a theory of literature which implies an ontology of time. We advance that, by identifying myth with romantic literature, Schlegel’s argumentative economy leads him to apply the metaphysical predicates of myth to romantic literature as such. We propose then to read the status of literary forms as constituting the substance which precedes them but, paradoxically, only exists through them

Human Ecology Economics (HEE) and Strategic Management

Human Ecology Economics (HEE) draws on evolutionary and complex systems processes by incorporating interdisciplinary material from the humanities and sciences. Lessons for strategic managers follow from this HEE perspective with examples from the banking industry. HEE can nurture a broad environmental perspective among strategic managers and an ontological understanding of their organization within its dynamic ecology. Reconciliation is attempted between the chaotic dualities inherent in strategic management (SM)

The question concerning the environment: a Heideggerian approach to environmental philosophy : a thesis presented in partial fulfillment of the requirements for the degree of Master of Arts in Philosophy at Massey University

This thesis will engage with the thinking of Martin Heidegger in order to show that our environmental problems are the necessary consequences of our way of 'knowing' the world. Heidegger questions the abstract, theoretical approach that the Western tradition has to 'knowledge', locating 'knowledge' in the human 'subject', an interior self, disengaged from and standing over against the other-than-human world, as external 'object'. Such an approach denies a voice to the other-than-human in the construction of 'knowledge'. Heidegger maintains that we are not a disembodied intellect, but rather we are finite, self-interpreting beings, embodied in a physical, social and historical context, for whom things matter. In view of this, he discards traditional notions of 'knowledge', in favour of understanding and interpretation. Accordingly, he develops what can be called a dialectical ontology, whereby we come to understand and interpret ourselves and other beings in terms of our involved interactions. This involved understanding acknowledges the participation of other-than-human beings in constructing an interpretation of the world, giving them a voice. Following Heidegger's way of thinking, I suggest that by developing an ontological-ethic, a way of dwelling-in-the-world based on a responsive engagement with other-than- human entities, we can disclose a world that makes both the other-than- human and humanity possible

The Measure of All Gods: Religious Paradigms of the Antiquity as Anthropological Invariants

Purpose of the article is the reconstruction of ancient Greek and ancient Roman models of religiosity as anthropological invariants that determine the patterns of thinking and being of subsequent eras. Theoretical basis. The author applied the statement of Protagoras that "Man is the measure of all things" to the reconstruction of the religious sphere of culture. I proceed from the fact that each historical community has a set of inherent ideas about the principles of reality, which found unique "universes of meanings". The historical space acquires anthropological properties that determine the specific mythology of the respective societies, as well as their spiritual successors. In particular, the religious models of ancient Greece and ancient Rome had a huge influence on formation of the worldview of the Christian civilization of the West. Originality. Multiplicity of the Olympic mythology contributed to the diversity of the expression forms of the Greek genius, which manifested itself in different fields of cultural activity, not reducible to political, philosophical or religious unity. The poverty of Roman mythology was compensated by a clear awareness of the unity of the community, which for all historical vicissitudes had always remained an unchanging ideal, and which was conceived as a reflection of the unity of the heavens. These two approaches to the divine predetermined the formation of two interacting, but conceptually different anthropological paradigms of Antiquity. Conclusions. Western concepts of divinity are invariants of two basic theological concepts – "Greek" (naturalism and paganism) and "Roman" (transcendentalism and henotheism). These are ideal types, so these two tendencies can co-exist in one society. The Roman trend continued to be realized by the anti-Roman religion, which took Roman forms and Roman name. Iconoclasm was a Byzantine version of the Reformation, promoted by the Isaurian emperors and failed due to the strong Hellenistic naturalistic lobby. Modern "Romans" are trying to get rid of the last elements of religious naturalism, and modern "Greeks" are trying to preserve the Hellenic elements in Christianity. Patterns can be transformed, but the observational view will still be able to identify their lineage. The developed model allows a deeper understanding of the culture of both ancient societies, as well as the outlook of Western man

Recent Hegel Literature: General Surveys and the Young Hegel

This is an offprint version of the article published in Telos (1980). The version made available in Digital Common was supplied by the author and is made available with permission of the publisher, Telos Press.Publisher's Versiontru

From human rights to person rights : legal reflections on posthumanism and human enhancement

In the intersection between law, science and technology lies the debate on the overcoming of the boundaries of the biological structure of the human being and its implications on the idea of human rights, on the concept of person and on the conception of equality – being the latter a fundamental tenet of a democracy. Posthumanism assumes a biological inadequacy of the human body regarding the quantity, complexity and quality of information which it can muster. The same occurs with the needs of accuracy, speed or strength demanded by the contemporary environment. Under such perspective, the body is considered to be an inefficient structure, with a short lifespan, easy to break and hard to fix. The body, always seen as the locus for the definition of human, emerges as the object of a commodification process that seeks to exonerate men from their burden - by declination towards a virtual existence, totally free and rational - or to enhance them with bionic devices or drugs. This issue has already been the subject of attention by many scholars like Savulescu, Rodotà, Broston, Fukuyama and even Habermas. Therefore, the aim of this paper is to seek, by criticism and revision of the positions on the foreseen problems of this process, an adequate theoretical approach on issues like the concept of person and its connection with the idea of human rights in order to promote the fundamental statement that all men are equal without disregard to the values of diversity and personal identity

Knowledge extraction from fictional texts

Knowledge extraction from text is a key task in natural language processing, which involves many sub-tasks, such as taxonomy induction, named entity recognition and typing, relation extraction, knowledge canonicalization and so on. By constructing structured knowledge from natural language text, knowledge extraction becomes a key asset for search engines, question answering and other downstream applications. However, current knowledge extraction methods mostly focus on prominent real-world entities with Wikipedia and mainstream news articles as sources. The constructed knowledge bases, therefore, lack information about long-tail domains, with fiction and fantasy as archetypes. Fiction and fantasy are core parts of our human culture, spanning from literature to movies, TV series, comics and video games. With thousands of fictional universes which have been created, knowledge from fictional domains are subject of search-engine queries - by fans as well as cultural analysts. Unlike the real-world domain, knowledge extraction on such specific domains like fiction and fantasy has to tackle several key challenges: - Training data: Sources for fictional domains mostly come from books and fan-built content, which is sparse and noisy, and contains difficult structures of texts, such as dialogues and quotes. Training data for key tasks such as taxonomy induction, named entity typing or relation extraction are also not available. - Domain characteristics and diversity: Fictional universes can be highly sophisticated, containing entities, social structures and sometimes languages that are completely different from the real world. State-of-the-art methods for knowledge extraction make assumptions on entity-class, subclass and entity-entity relations that are often invalid for fictional domains. With different genres of fictional domains, another requirement is to transfer models across domains. - Long fictional texts: While state-of-the-art models have limitations on the input sequence length, it is essential to develop methods that are able to deal with very long texts (e.g. entire books), to capture multiple contexts and leverage widely spread cues. This dissertation addresses the above challenges, by developing new methodologies that advance the state of the art on knowledge extraction in fictional domains. - The first contribution is a method, called TiFi, for constructing type systems (taxonomy induction) for fictional domains. By tapping noisy fan-built content from online communities such as Wikia, TiFi induces taxonomies through three main steps: category cleaning, edge cleaning and top-level construction. Exploiting a variety of features from the original input, TiFi is able to construct taxonomies for a diverse range of fictional domains with high precision. - The second contribution is a comprehensive approach, called ENTYFI, for named entity recognition and typing in long fictional texts. Built on 205 automatically induced high-quality type systems for popular fictional domains, ENTYFI exploits the overlap and reuse of these fictional domains on unseen texts. By combining different typing modules with a consolidation stage, ENTYFI is able to do fine-grained entity typing in long fictional texts with high precision and recall. - The third contribution is an end-to-end system, called KnowFi, for extracting relations between entities in very long texts such as entire books. KnowFi leverages background knowledge from 142 popular fictional domains to identify interesting relations and to collect distant training samples. KnowFi devises a similarity-based ranking technique to reduce false positives in training samples and to select potential text passages that contain seed pairs of entities. By training a hierarchical neural network for all relations, KnowFi is able to infer relations between entity pairs across long fictional texts, and achieves gains over the best prior methods for relation extraction.Wissensextraktion ist ein Schlüsselaufgabe bei der Verarbeitung natürlicher Sprache, und umfasst viele Unteraufgaben, wie Taxonomiekonstruktion, Entitätserkennung und Typisierung, Relationsextraktion, Wissenskanonikalisierung, etc. Durch den Aufbau von strukturiertem Wissen (z.B. Wissensdatenbanken) aus Texten wird die Wissensextraktion zu einem Schlüsselfaktor für Suchmaschinen, Question Answering und andere Anwendungen. Aktuelle Methoden zur Wissensextraktion konzentrieren sich jedoch hauptsächlich auf den Bereich der realen Welt, wobei Wikipedia und Mainstream- Nachrichtenartikel die Hauptquellen sind. Fiktion und Fantasy sind Kernbestandteile unserer menschlichen Kultur, die sich von Literatur bis zu Filmen, Fernsehserien, Comics und Videospielen erstreckt. Für Tausende von fiktiven Universen wird Wissen aus Suchmaschinen abgefragt – von Fans ebenso wie von Kulturwissenschaftler. Im Gegensatz zur realen Welt muss die Wissensextraktion in solchen spezifischen Domänen wie Belletristik und Fantasy mehrere zentrale Herausforderungen bewältigen: • Trainingsdaten. Quellen für fiktive Domänen stammen hauptsächlich aus Büchern und von Fans erstellten Inhalten, die spärlich und fehlerbehaftet sind und schwierige Textstrukturen wie Dialoge und Zitate enthalten. Trainingsdaten für Schlüsselaufgaben wie Taxonomie-Induktion, Named Entity Typing oder Relation Extraction sind ebenfalls nicht verfügbar. • Domain-Eigenschaften und Diversität. Fiktive Universen können sehr anspruchsvoll sein und Entitäten, soziale Strukturen und manchmal auch Sprachen enthalten, die sich von der realen Welt völlig unterscheiden. Moderne Methoden zur Wissensextraktion machen Annahmen über Entity-Class-, Entity-Subclass- und Entity- Entity-Relationen, die für fiktive Domänen oft ungültig sind. Bei verschiedenen Genres fiktiver Domänen müssen Modelle auch über fiktive Domänen hinweg transferierbar sein. • Lange fiktive Texte. Während moderne Modelle Einschränkungen hinsichtlich der Länge der Eingabesequenz haben, ist es wichtig, Methoden zu entwickeln, die in der Lage sind, mit sehr langen Texten (z.B. ganzen Büchern) umzugehen, und mehrere Kontexte und verteilte Hinweise zu erfassen. Diese Dissertation befasst sich mit den oben genannten Herausforderungen, und entwickelt Methoden, die den Stand der Kunst zur Wissensextraktion in fiktionalen Domänen voranbringen. • Der erste Beitrag ist eine Methode, genannt TiFi, zur Konstruktion von Typsystemen (Taxonomie induktion) für fiktive Domänen. Aus von Fans erstellten Inhalten in Online-Communities wie Wikia induziert TiFi Taxonomien in drei wesentlichen Schritten: Kategoriereinigung, Kantenreinigung und Top-Level- Konstruktion. TiFi nutzt eine Vielzahl von Informationen aus den ursprünglichen Quellen und ist in der Lage, Taxonomien für eine Vielzahl von fiktiven Domänen mit hoher Präzision zu erstellen. • Der zweite Beitrag ist ein umfassender Ansatz, genannt ENTYFI, zur Erkennung von Entitäten, und deren Typen, in langen fiktiven Texten. Aufbauend auf 205 automatisch induzierten hochwertigen Typsystemen für populäre fiktive Domänen nutzt ENTYFI die Überlappung und Wiederverwendung dieser fiktiven Domänen zur Bearbeitung neuer Texte. Durch die Zusammenstellung verschiedener Typisierungsmodule mit einer Konsolidierungsphase ist ENTYFI in der Lage, in langen fiktionalen Texten eine feinkörnige Entitätstypisierung mit hoher Präzision und Abdeckung durchzuführen. • Der dritte Beitrag ist ein End-to-End-System, genannt KnowFi, um Relationen zwischen Entitäten aus sehr langen Texten wie ganzen Büchern zu extrahieren. KnowFi nutzt Hintergrundwissen aus 142 beliebten fiktiven Domänen, um interessante Beziehungen zu identifizieren und Trainingsdaten zu sammeln. KnowFi umfasst eine ähnlichkeitsbasierte Ranking-Technik, um falsch positive Einträge in Trainingsdaten zu reduzieren und potenzielle Textpassagen auszuwählen, die Paare von Kandidats-Entitäten enthalten. Durch das Trainieren eines hierarchischen neuronalen Netzwerkes für alle Relationen ist KnowFi in der Lage, Relationen zwischen Entitätspaaren aus langen fiktiven Texten abzuleiten, und übertrifft die besten früheren Methoden zur Relationsextraktion