Adam Pease and Christiane Fellbaum Presenter: 吳怡安 Formal ontology as interlingua: the SUMO and WordNet linking project and global WordNet Adam Pease and Christiane Fellbaum Presenter: 吳怡安

Outline 2.1 WordNet 2.1.1 Types and instances 2.1.2 Formal vs linguistic relations 2.1.3 Lexical vs conceptual ontologies 2.1.4 SUMO 2.2 Principles of construction of formal ontologies and lexicons 2.3 Mappings 2.4 Interpreting language 2.5 Global WordNet 2.5.1 The Interlingual Index 2.6 SUMO translation templates

2.1 WordNet WordNet is a large lexical database for English Basic unit: synset (cognitively equivalent synonyms) Eg. {vacation, holiday} Definition: leisure time away from work devoted to rest or pleasure Sentence:"we get two weeks of vacation every summer” 117 000 synsets Relations Super-subordinate relation (also called hyperonymy, hyponymy) Transitive: armchair-chair-furniture Part-whole relation (Meronymy, holonym) verbs towards the bottom of the trees express increasingly specific manners characterizing an event (communicate-talk-whisper)

2.1.1 Types and instances WordNet distinguishes among Types (common nouns) and Instances (specific persons, countries and geographic entities). armchair is a type of chair Barack Obama is an instance of a president Instances are always leaf (terminal) nodes in their hierarchies. However, other distinctions are lacking. Brother and architect as Types of persons Dwarf is a kind of person One can refer to the same person as both a dwarf and an architect Roles often refer to professions or functions associated with a person or temporary states (such as patient)

2.1.2 Formal vs linguistic relations One could extend the a few relations of WordNet to all the hundreds of relations that are found in a formally specified logical theory like SUMO. Eg. part-of, beforeOrEqual, authors etc. Relating informal linguistic notions with more formal ontological relations Specifying complex relations that cannot be captured explicitly as simple links

2.1.3 Lexical vs conceptual ontologies Lexicon can be defined as the mappings of concepts onto words. There are structural gaps where the geometry of the relations would require a word, yet where the language does not have one the class of wheeled vehicles (like cars and motorbikes) vs vehicles that run on rails (trains, trams) Crosslinguistic differences in lexicalization patterns kinship relations Existing words do not fully reflect the inventory of concepts that is available, so one can use the non-lexical ontology such as SUMO

2.1.4 SUMO (1) The Suggested Upper Merged Ontology (SUMO) is a formal ontology stated in a first-order logical language called SUO-KIF. Upper ontology includes general notions in common-sense reality time, spatial relations, physical objects, events and processes Mid-Level Ontology (MILO): more specific Domain ontologies cover over a dozen specific areas world government, finance and economics, and biological viruses

2.1.4 SUMO (2) 1,000 terms and 4,000 axioms (which includes 750 rules) Term: named concept Axiom: any statement in logic Rule: a particular kind of axiom that has two parts: an antecedent and a consequent http://www.ontologyportal.org (<=> (earlier ?INTERVAL1 ?INTERVAL2) (before (EndFn ?INTERVAL1) (BeginFn ?INTERVAL2)))

2.1.4 SUMO (3) In a formal ontology, it is solely the axioms as mathematical statements that give the terms their meaning. The meaning of the terms can be tested for consistency automatically with an automated theorem prover. The names of terms in SUMO are just convenient labels, so there are no synonymy.

2.2 Principles of construction of formal ontologies and lexicons Lexicon must accurately reflect the inventory and use of words in a given language. Neither eliminated nor ‘missing’ words By contrast, an ontology is an engineered product. Naming, categorization, creation of the terms are at will Every lexicalized concept should be covered by a term. Synonymy is not needed The names of the terms could be replaced by arbitrary unique character strings and their meaning would still be the same. In a formal ontology, meaning is determined only by the formal axioms.

2.3 Mappings (1) Two phases: First, mapping just SUMO itself to WordNet. Three types of mappings were employed: rough equivalence, subsuming, and instance. Equivalence: { artificial_satellite } to ArtificialSatellite Subsuming: { elk } to HoofedMammal Instance: { george_washington } to Human Second, for each synset that occurred three or more times in SemCor, we also created a new concept in the MILO if one did not already exist in SUMO.

2.3 Mappings (2) Limitation: a single mapping from a lexical entity to a formal term does not fully capture the meaning of some lexical items Eg. { Continue } can refer to many unrelated types of Process referenced in the context of previous sentences One would need a more complex relation structure to express the semantics of this lexical item

2.4 Interpreting language Deep semantic interpretation of language Eg. ‘Brutus stabbed Caesar with a knife on Tuesday.’ (exists (?S ?K ?T) (and (instance ?S Poking) (instance ?K Knife) (instance ?T Tuesday) (agent ?S Brutus) (patient ?S Caesar) (time ?S ?T) (instrument ?S ?K))) (=> (instance ?X Knife) (capability Cutting ?X instrument))

2.5 Global WordNet Vossen (1998) coordinated the effort to create eight European wordnets that follow a common design and are interlinked via an Interlingual Index (ILI) Wordnets exist in over 40 languages spoken around the world at present. Interconnected wordnets hold great potential for crosslinguistic applications. Shedding light on commonalities and the differences in the ways languages map concepts onto words

2.5.1 The Interlingual Index there are language-specific ‘lexical gaps’ there are differences in the ways languages structure their words and concepts The ILI initially consisted of all English WordNet synsets. Each international wordnet either links its synsets to the matching synsets in the ILI or adds a synset that is not yet in the ILI. Each synset in the language-specific wordnet has at least one equivalence relation to an entry in the ILI. Due to the limitations of lexical ontologies, many wordnets have also been linked to SUMO.

2.6 SUMO translation templates In order to make SUMO more understandable, they created a system that performs rough natural-language paraphrasing of the formal axioms (<=> (earlier ?INTERVAL1 ?INTERVAL2) (before (EndFn ?INTERVAL1) (BeginFn ?INTERVAL2))) A time interval happens earlier than another time interval if and only if the end of the time interval happens before the beginning of the other time interval.

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