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![Page 1: Synergy between Ontologization and Quality Management Michael Ellsworth, ICSI, Berkeley (Joint work with Jan Scheffczyk)](https://reader035.fdocuments.us/reader035/viewer/2022062713/56649cdf5503460f949a92ed/html5/thumbnails/1.jpg)
Synergy between Ontologization and Quality Management
Michael Ellsworth,
ICSI, Berkeley
(Joint work with Jan Scheffczyk)
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1. Defining Quality Management
2. The necessity of ontology: The story of FE fillers
3. Metonymy: what ontologies don’t have
4. Ontologies need metonymy; does metonymy need ontologies?
![Page 3: Synergy between Ontologization and Quality Management Michael Ellsworth, ICSI, Berkeley (Joint work with Jan Scheffczyk)](https://reader035.fdocuments.us/reader035/viewer/2022062713/56649cdf5503460f949a92ed/html5/thumbnails/3.jpg)
1. Defining Quality Management
2. The necessity of ontology: The story of FE fillers
3. Metonymy: what ontologies don’t have
4. Ontologies need metonymy; does metonymy need ontologies?
![Page 4: Synergy between Ontologization and Quality Management Michael Ellsworth, ICSI, Berkeley (Joint work with Jan Scheffczyk)](https://reader035.fdocuments.us/reader035/viewer/2022062713/56649cdf5503460f949a92ed/html5/thumbnails/4.jpg)
Defining Quality Management for FN
• How well do data correspond to what they should be
• How do the data correspond to our expectations– Considering only expectations based on our
definitions of data categories
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Simple example
• The semantic type “Non_lexical_frame” on a frame should mean that the frame has no evoking lexical units, and is purely for frame relations
• NB: The lack of this ST should signify that there are lexical units
• (Used, e.g., to remind frame-makers to add at least 1 LU, non-lexical frames excluded)
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Automating QM
• Data is human-produced, so definitions of the data categories are designed to be understood by humans
• But! There is too much data to inspect every piece
• Automation requires formally or operationally defining the data categories
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Formalizing data-category definitions
• Iff F, instance of a frame, and not T, instance of “Non_lexical_frame”, s.t. T is an ST of F, then L, where L is an LU of F
• Presupposition: “Non_lexical_frame” should not mark anything other than a frame
• Usage restriction: All non-lexical frames should have at least two frame-to-frame relations to lexical frames
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CDET (plus “glue”)
• Quality definitions in first-order logic can be evaluated with CDET (Scheffczyk 2004)
• If the fix is already known, CDET can automatically correct inconsistencies (not implemented for FrameNet)
• Otherwise, CDET produces a report on the inconsistencies with enough information for a user to understand and correct the problem
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1. Defining Quality Management
2. The necessity of ontology: The story of FE fillers
3. Metonymy: what ontologies don’t have
4. Ontologies need metonymy; does metonymy need ontologies?
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What’s ontology got to do with it?
• Broadly: the process of formalizing data category definitions is ontologization
• But also: formal connection to “official” ontologies and/or WordNet is necessary– Other resources have formalizations that
FrameNet doesn’t
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More complex requirement
• The phrases that fill frame elements should denote the kind of entity specified by the semantic type on the frame element– She batted her eyelashesBody_part.
– Here the Body_part frame element is required to have the semantic type “Body_part”
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Formalizing
• The semantic head of a filler phrase should be interpretable as a subtype of the FrameNet Semantic Type– So eyelashes in the above example must be a
subtype of “Body_part”
• But! Most fillers of FEs (pronouns, entity nouns, names) are not described in FrameNet itself
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WordNet
• WordNet has coverage of a very large number of word-senses
• Word senses, via the connection to synsets, are hierarchically connected via the “is-a” relation, so subtypes are determinable
• WordNet does not have synset nodes to cover all FN semantic types
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Wrinkle: Finding headwords
• Subtracts preposition and uses headwords from Minipar
• For relative clauses– substitutes the antecedent phrase for relative– It had a sharp pointed face and a feathery tailAnt thatRel arched over its back.
• Ought to take account of transparent nouns– One of his eyebrows arched ironically.– One is a quantifier; eyebrows is the category
• Ought to handle conjunction
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Which synset for polysemous words?
• Most appropriate synset highly dependent on genre and frame element
• Therefore: we use all possible synsets
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SUMO connects semantic types and WN
• FrameNet semantic types correspond relatively well to SUMO concepts (see PDF1)
• Cases of mismatch are handled with new nodes defined in SUO-KIF (the language of SUMO) connecting to pre-existing SUMO concepts
• WordNet is already mapped to SUMO (Niles & Pease 2003)
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Headwords not in WordNet
• Pronouns– Ex: SheAgent swung her head in his direction.
– She, he, who, etc. connected to SUMO Sentient_agent
• Named entities – Depending on NEs used, readily mappable to
SUMO
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Prepositions
• Currently subtracted and not analyzed• Correct for marker prepositions; noun’s type is
assigned regardless of preposition or lack of preposition:– He gives money to local charities.– I’m just going to give her some milk.– You’re doing it for the child she’s foisting on you.
• This is incorrect for relation-defining prepositions:– We walked together to the cab.– To here correctly maps to the SUMO node Goal
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Actual errors
• Rare!– E.g.: He swung himselfBody_part around the
corner …
• Himself maps to SUMO Sentient_agent, which is not consistent with Body_part
• The above sentence actually evokes Cause_ to_move_in_place
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1. Defining Quality Management
2. The necessity of ontology: The story of FE fillers
3. Metonymy: what ontologies don’t have
4. Ontologies need metonymy; does metonymy need ontologies?
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Assailants, Victims, and Metonymy
• The method so far does not correctly account for many other FEs in other frames
• E.g. the Assailant FE, especially so in a narrow genre– For the following, annotation of text from the
Nuclear Threat Initiative and related texts is used
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Background:
• Assailant has the semantic type Sentient, mapped to SUMO Sentient_agent
• The most common fillers of the Assailant FE of the Attack frame are as follows
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Filler Headword Frequency
It It 3
Its Its 3
Iraqi Iraqi 2
Iran Iran 2
Terrorist Terrorist 2
The US US 2
Iraq Iraq 1
Al-Qaida Al-Qaida 1
His forces Force 1
By Iraq Iraq 1
US US 1
U.S. U.S. 1
Chadian forces Force 1
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This results in the following hierarchy:
(See PDF2)
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• The problem:– 38% of the fillers evoke the Nation concept in SUMO
– Nation is not a subtype of Sentient_agent
• Clash with linguistic intuition: fillers like “Iraq” are completely unobjectionable as Assailants
• Since we know Iraq is a legitimate instance of SUMO Nation, and yet it fits, the problem could be only be in the SUMO hierarchy (no) or in FN’s semantic type assignment…
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Poorly fitting types? Disjunctive Types?
• Lifting the FN semantic type to a more general level connects it to the SUMO Agent node, covering Nation– But this also covers Geopolitical_area (etc.),
including things like city and senate district that are very unlikely to launch literal attacks
• Or should we make a disjunctive type?
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… or not!
• All instances of Attack require that there be some actual person(s) filling the Assailant role:– The initial Iraqi attack destroyed most of the
Kuwaiti jet fighters.
• This implicates the following:– A person or people empowered to act for Iraq
made an attack.
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Metonymy
• The implication that a covert entity (the people) fills the same role as a related overtly mentioned entity (Iraq) is the hallmark of metonymy
• Metonymy is pervasive:– Where am I (= my car) parked?– Alternations like possession (relation) and
possession (something in that relation)
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Adding Metonymy to the Ontology?
• The solution to the above quandary is to add in an explicit metonymy link to the ontology connecting Nation to People
• Metonymy is normally contextually limited– By Frame and FE
• ##The nation kissed her/them
– At least statistically, also by genre• Nations don’t occur as Assailant in general domain
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Metonymy unloved?
• Some associated axioms would involve a difficult-to-define relation of association and subtypes thereof
• Given its contextual dependence, metonymy is unlikely to win the acceptance of run-of-the-mill ontologists, who want fixed facts, not fixed meta-facts
• Axioms concerning communication itself could encode contextual dependence
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Metaphor
• May also change selectional restrictions drastically– I chewed on the question for a few days.
• But not always– She shoved several superiors out of her way in
her climb to the top.
• Similarly contextual to metonymy
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1. Defining Quality Management
2. The necessity of ontology: The story of FE fillers
3. Metonymy: what ontologies don’t have
4. Ontologies need metonymy; does metonymy need ontologies?
![Page 33: Synergy between Ontologization and Quality Management Michael Ellsworth, ICSI, Berkeley (Joint work with Jan Scheffczyk)](https://reader035.fdocuments.us/reader035/viewer/2022062713/56649cdf5503460f949a92ed/html5/thumbnails/33.jpg)
Ontologies and language
• Ontologists clearly see the need to connect to language– Ease of accessability concerns with ontologies– Connections to WordNet
• Unclear if ontologies can ever have a reasonable interface with language without coming to grips with metaphor and metonymy
• Unclear if current ontologies can incorporate these notions
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Ontologies and language?
• There are other vital and pervasive aspects of language-based reasoning absent from ontologies:– Fuzzy, radial categories– Use of underspecification– Contextuality
• Are these difficulties sufficient grounds to discard ontologies?
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Language-based Ontology
• Ontologies (or something) will be necessary for reasoning
• Older ontologies may have great difficulty incorporating language in any deep way
• Newer ontologies, some of which seem to be built on more convenient principles (e.g. the Generic Concept Library), might be more attractive
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FIN
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Kinds of Contradictions
• When the data have well-defined properties that bear on other data:– The data can be directly checked against itself
– Such checks already largely implemented with CDET
• When the data have properties that are only confirmable by outside knowledge:– The data can only be checked if the outside knowledge
can somehow be accessed by the automated checker
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