Bach, 1998: Ambiguity is a property of linguistic expressions.
Bernheim, 1998: Strategic ambiguity is contractual incompleteness arising from limits on public verifiability of aspects of performance, combined with strategic opportunities created by contract terms.
Chávez, 1996: Ambiguity = vagueness = "uncertainty about probability, created by information that is missing and knowable". Empirically, "risk aversion and ambiguity aversion are independent". People are willing to pay an "ambiguity premium" to avoid ambiguity, even when its avoidance has no effect on their optimal action or on the outcome.
Dobbs, 1991: Ambiguity is an agent's uncertainty as to the probabilities of alternative outcomes (states) in some set, such that the agent can make a best guess.
Dušková, 1995: Ambiguity is "a property of sentences, not of separate lexical items or grammatical forms. For ambiguity to arise, there has to be a field of relations that can be interpreted in more than one way." Ambiguity differs from homonymy and from neutrality (vagueness).
Epstein, 2004: Ambiguity is uncertainty about the implication of a signal for the distribution of probabilities of a set of possible future states. That which is ambiguous is information.
Fox, 1995: Ambiguity = vagueness = imperfect information about probabilities. Perfect information about probabilities = risk.
Hasida, 1995, 1996a, 1996b: A speaker and a hearer are modeled as playing a communication game in which they both benefit from the hearer understanding the speaker's intent, even if the speaker intends to deceive the hearer, but in which the speaker also benefits by not incurring the cost of disambiguation. The game's outcome also depends on whether the parties can coordinate their interpretations of ambiguous utterances.
Hoefler, 2005b: Ambiguity is a property of languages, grammars, sentences, phrases, and lexemes. "A grammar is ambiguous if some string has more than one parse tree". "A language is inherently ambiguous if every grammar for it is ambiguous."
Monz, 1999: Formal model of ambiguity in a multiagent system. Ambiguity is existence of multiple nonequivalent semantic representations of a statement. Actual ambiguity of a statement is distinct from an agent's perception that the statement is ambiguous. Statements are formally constrained in ways intended to represent maxims of quality, quantity, and manner (avoid ambiguity).
Oepen, 2002: Redwoods treebanks record all disambiguating decisions of annotators and use multiple annotators per sentence. (This would permit defining operationalizable measures of ambiguity of sentences. In the Verbmobil treebanks, discourses are recorded, permitting access to contexts of ambiguities. But discourses seem to average about 30 sentences long, far longer than minimal relevant contexts.)
Wasow, 2003: An ambiguous expression has 2 or more disjoint denotations.
Bruening, 2004: Ambiguity of sentences with reciprocal verbs may vary among language types, e.g. less with head finality.
Clark, 1996: Notion of meaning suggests that ambiguity is not universally uniform, if combined with other research showing cross-linguistic differences in indirection, formality, and idiom. In fact, it suggests ambiguity is highly individual: "X did Y" may have a shared literal meaning in the speech community, but its actional meaning is presumably idiosyncratic, something people learn about one another. This raises question: What kind of meaning do people expect machines to reason on and translate? Do they make the extreme Nass-Reeves anthropomorphic assumption? If not, how do they dehumanize their expectations?
Dayal, 2004: The conditions under which nominals are ambiguous between (1) definite or indefinite identifiers and (2) kinds differ (perhaps predictably) among languages.
Dor, 2000: A language's syntax is largely constrained by that language's "linguistic semantics", making it possible in any language to express "a constrained subset of meanings" (p. 349) out of the larger set of meanings that the language's speakers can conceptualize (based on research and arguments of Rappaport-Hovav, Levin, Levinson, Frawley, and Dor). The semantic differences dictating syntactic constraints (e.g., verb classes) are generally subtle and beyond speaker awareness. The constraints are also language-specific. (This seems to imply that languages differ in their admissible interpretations of an underspecified expression.)
Gilboy, 1995: Human ambiguity resolution has been hypothesized to be governed by universal principles, such as late closure (causing "which" in "the X of the Y which ..." to be interpreted as referring to Y, not X). Some have also found such principles not being universal, but differing between languages. New experiments support a mixed hypothesis that sententially primary constructions are subject to purely structural and universal rules of attachment interpretation, while sententially secondary constructions are subject to multiple and not necessarily universal principles, with different details of the utterances leading hearers to adopt different interpretations.
Grabowski, 1996: Experimental subjects' interpretations of ambiguous spatial prepositions as deictic or intrinsic differ among 5 languages, and the differences can be explained partly by the differences among the languages' prepositional inventories. There are 2-, 3-, and 4-preposition languages with respect to relative locations on the primary horizontal and temporal axes.
Hawkins, 2004: Categorial ambiguity varies (or is predicted to vary) among languages in direct relation to disambiguating particles (p. 88).
Hoefler, 2005a: Ambiguity is hypothesized to exist because it facilitates language learning and languages evolve to be learnable.
Horie, 2002: The incidence of ambiguity differs between languages (Japanese and Korean) consistently with their typical speakers' attitudes toward propositional precision in linguistic encoding, Koreans being more literal than Japanese.
Li, 1993: Compound verbs denoting a causing action and its effect are ambiguous in Chinese with respect to whether the subject or the object is the effect experiencer, but unambiguous in Japanese, where only the subject is the experiencer.
Pirkola, 2001: Languages differ in frequency of lexical ambiguity, e.g. English > German, English > Chinese (p. 18).
Ruch, 2000: A general corpus is more lexically ambiguous than a medical one.
Tatevosov, 2001: Describes syntactic ambiguities between habitual present and future time (dependent on individual-level versus stage-level predication) in Andic languages. Example of language-specific ambiguities.
Al-Najjar, 2005: Undescribable events: a property of theoretical contracts. Infinite complexity of potential state of world makes its description prohibitively costly in contracts.
Bach, 1998: types = {lexical, structural}, {act/object, type/token, process/product, scope}. Relatives = {vagueness, unclarity, inexplicitness, indexicality, semantic underdetermination, lexical underdetermination, nonliterality, indirection, homonymy}.
Barker, 2002: Vagueness includes predication that is imprecise as to degree (e.g., "X is tall"). Any assertion that includes such a predication may give factual or metalinguistic information.
Battigalli, 2002: Incompleteness: a property of theoretical and empirical contracts and instructions (with or without conflict of interest). Caused by costs of description. Types: {discretion, rigidity}.
Berry, 2003: Multiple types and subtypes from linguistic and legal theories.
Ceccato, 2004: Types and subtypes of ambiguity are:
Clark, 1996: Models language use in a way that makes ambiguity ubiquitous but problematic, since it is impossible to define the meaning of any expression. Any expression joins with other elements of action of the speaker and others to convey multiple things, such as beliefs, intentions, expectations, wishes, preferences, and promises. The meaning is not compositional.
Dayal, 2004: The conditions under which nominals are ambiguous between (1) definite or indefinite identifiers and (2) kinds are complex.
Dušková, 1995: "Syntactic ambiguity is defined as a property of sentences arising from multiple interpretations of a field of syntactic relations. Although a wide range of ambiguities in English have analogous counterparts in Czech, various types of homonymy in English create ambiguous sentences with Czech counterparts for each reading. Among the latter are those due to homonymy of (1) subordinate clause types introduced by a wh-phrase, (2) subordination functions including successive modification, (3) universal quantifier scope in sentences with total negation, (4) the sentence position of prepositions & particles, & (5) postmodifying & adverbial functions. Ambiguities due to the absence of formal indicators of case & verbal categories in English are also exemplified."
Eggleston, 2000: Contracts have values on "completeness" and on "complexity". Completeness has 2 types: p-completeness and f-completeness. Assume a contract specifies payoffs to both parties under various future states. P-completeness is the specification of all payoff-relevant states and their respective payoffs, and f-completeness is the specification of all verifiable ones. Complexity has 3 dimensions, 1 of which is the multiplicity of states for which payoffs are itemized. So, a contract can be incomplete but complex on that dimension if there are many payoff-relevant states and the contract specifies payoffs for many of them but still not for all. And it can be complete but simple if it specifies payoffs for all states but there aren't many (or many verifiable ones).
Gifford, 1999: A contract's completeness is the extent to which it specifies an action for an event. Parties to a contract are assumed able to make it complete but to decide how much of their limited attention to allocate to advancing its completeness as an alternative to doing so for other contracts.
Hawkins, 2004: Ambiguity is the assignment of multiple conventionally specified properties to the same form. Vagueness is the assignment to a form of a property that has many non-conventionalized extensions. Zero specification is the assignment of a completely underspecified attribute to a form. See pp. 39-40.
Hoefler, 2005b: Ambiguity types: {nonstructural, structural}. Nonstructural ambiguity types: {pragmatic, lexical}. Lexical ambiguity types: {homonymy, polysemy}. Structural (compositional) ambiguity types: {syntactic, semantic}. Syntactic ambiguity types: {attachment, referential, categorial}. Semantic ambiguity types: {scope, plural}. All ambiguity types can exist in compositional languages; structural ambiguity can exist in compositional languages, but not in holistic languages.
Hutchins, 1992: Ambiguity types: {morphological, lexical, structural}, {monolingual, transfer}, {real, systemic}. Morphological ambiguity is ambiguity with respect to the morphological analysis of a word, i.e. where the morpheme boundaries are. Lexical ambiguity types: {categorial ambiguity, homography, polysemy}. Structural ambiguity includes quantifier scope ambiguity. Ambiguity is defined as distinct from anaphora antecedent uncertainty, but "anaphora can be thought of as a sort of ambiguity" (p. 95).
Norvig, 1987: Traditional "dimensions" (but aren't these really types?) of ambiguity are:
Lexical ambiguity is further describable on the dimension (types?) of polysemy versus homonymy.
Trujillo, 1999: Sources of ambiguity include part of speech, syntactic structure, word sense, scope, anaphora, definite reference, and ellipsis. Stages at which disambiguation is necessary in machine translation are analysis, transfer, and generation.
Wasow, 2003: Ambiguity versus vagueness = multiplicity of denotations versus unclear boundary of denotation. Types of ambiguity include lexical, syncretic, coordinational, scopal, unnamed (e.g., "The chicken is ready to eat"), complex (e.g., "Flying planes can be dangerous"), categorial, syntactic, attachment.
Yarowsky, 1996: Text-to-speech synthesis requires the resolution of lexical homographs classifiable into 7 major categories.
Arnold, 2004: Speakers under some conditions fail to use available syntactic or prosodic methods for disambiguation.
Bach, 1998: "Philosophers sometimes lament the prevalence of ambiguity in natural languages and yearn for an ideal language in which it is absent. But ambiguity is a fact of linguistic life."
Baker, 1994: Knowledge-based disambiguation of 3 English ambiguity types: PP attachment, NN compounds, and AN attachment (sec. 4.2). Then residual disambiguation by author.
Battigalli, 2002: Enrichment of language with contingency-specificying clauses.
Berry, 2003: Language formalization and regulation, context enrichment in utterances, definition of interpretation conventions, recognition and evasion of ambiguous expressions in natural language.
Blanchon, 1997: Automated interactive disambiguation by author interrogation, with language-independent engine and language-specific modules.
Ceccato, 2004: Prototype of a tool for interactive ambiguity detection and notification to author writing in a natural language described. It estimates sentential ambiguity and marks sentences whose estimated ambiguities exceed a threshold.
Chantree, 2003: Describes a concept for annotation of generated natural language to show how serious its sentences' estimated ambiguities are. Users would respond with their own estimates, and system would modify its future estimates accordingly.
Ferreira, 2000: Speakers in experiments failed to use syntactic means available for the avoidance of disruptive temporary ambiguities. This evidence also casts doubt on the hypothesis that parsing difficulty and generating difficulty coincide. But the experiments did not force awareness of parsing difficulty on subjects and they didn't exhibit such awareness, so it is unknown what ambiguity avoidance would take place if awareness existed. If and when speakers avoid ambiguity, there are several kinds of ambiguity (syntactic, referential, etc.) that they might simultaneously attend to and several modes (syntax, prosody, gesture, etc.) they might disambiguate in. Future research on ambiguity avoidance should become more realistic, as suggested by Clark.
Haywood, 2005: Speakers in dialog use disambiguating options in the grammar more where ambiguity risk is greater and more when others have done so.
Hawkins, 2004: The efficient design and use of languages maximize ambiguity consistent with the ability of the hearer to "enrich each set of property alternatives to a particular P in performance" (p. 48), because enrichment is inexpensive compared with complexity. (Argument is based on processing cost. Implies that if technology improves and changes some processing cost then language design and use will tend to change accordingly.)
Hutchins, 1992: Automatic ambiguity resolution for translation requires use of contextual knowledge, linguistic knowledge, and world knowledge. These together are generally insufficient because of inadequate implementation and because some utterances can't be disambiguated without private knowledge of the speaker, so an additional method is speaker interrogation.
Kamsties, 2001: Ambiguities in informal specifications can be detected with checklists and simulations based on analysis of the precision requirements.
Kraljic, 2005: Speakers disambiguate prosodically, but the evidence is mixed as to whether they do so even when unnecessary and why they do so.
Lapata, 2004: With simplifying assumptions, it is possible, in a parsed corpus, to estimate the prior probability distribution of the possible semantic classes of a verb token from its syntactic frame, by inference from the set of semantic classes of that verb and the distribution of syntactic frames of that verb in the corpus. Doing this can improve verb disambiguation.
Nerlich, 2001: Ambiguity and polysemy confer benefits and are employed for conversational purposes (humor, competition, solidarity, coordination, association, etc.), thus not considered as defects to be avoided. Linguistic encoding includes deliberate selection of formulations that have desired combinations of possible interpretations. (Cf. Norvig, 1987.)
Norvig, 1987: Behavior toward ambiguity evidences acceptance of multiple simultaneous interpretations. (Cf. Nerlich, 2001.)
Power, 1998: Describes a concept, WYSIWYM, and a prototype of it, under which domain experts make selections within and about natural-language text in order to edit knowledge, while the knowledge engine generates all the text.
Rodd, 2000: Experimentally, subjects can decide whether a sequence of characters is a word faster if it is polysemous than if it is monosemous, but slower if it is ambiguous than if it is unambiguous.
Scott, 1999: "Symbolic Authoring" is the encoding of a document by an author in a meaning-representation system with the aid of support software that incorporates a domain model. It results in the automatic production of multilingual representations of the content without risks of misinterpretation and without source-language bias. Examples of such software in use: EXCLASS (job descriptions), DRAFTER-I (software manuals), GIST (forms), Unnamed (patent claims).
Snedeker, 2003: Experimentally, speakers use prosodic cues to avoid ambiguity if, and only if, the linguistic ambiguity of a phrase remains after consideration of the referential scene. Listeners use prosodic disambiguation cues when present.
Temperley, 2003: Ambiguity avoidance, if it occurs, may be manifested as (a) grammatical rules, (b) regularities in syntactic choice ("strategic ambiguity avoidance"), or (c) ad-hoc reformulations of expressions that in their contextual facts would be ambiguous ("tactical ambiguity avoidance"). Inclusion of optional relative pronoun or complementizer in embedded object relative clauses in a sample of the Wall Street Journal (Penn Treebank) corpus supports the hypothesis that strategic ambiguity avoidance is practiced, but opposes the hypothesis that tactical ambiguity avoidance is practiced. Extensive discussion of anaphoric and other plausible considerations simultaneously affecting syntactic choices. Prior experimental literature summarized.
Trujillo, 1999: Describes and evaluates methods of disambiguation in machine translation (ch. 9). The "most promising" ones are statistical ones based on large corpora, but the problem is thought to be AI-complete.
Wasow, 2002: Describes reasons for hypothesizing that written text would exhibit ambiguity-avoiding syntactic choices and would do so more than speech, including writers' greater ability and readers' greater need. Constituent ordering was found in the Brown Corpus not to be explainable as motivated by ambiguity avoidance, so this motive seems unlikely to operate elsewhere. Minimal oral data were found in the Switchboard Corpus, and these are consistent with the above prediction. Experimentally, constituent order shifting that would disambiguate was even less frequent than constituent order shifting that wouldn't. Subjects' failure to avoid ambiguity is unexplained, but a plausible reason is that humans have and use enough diverse disambiguation cues to disambiguate successfully without constituent order shifting. (So, what happens if writers know this isn't the case in this situation?).
Wasow, 2003: Language evolution appears not to decrease ambiguity. Describes several hypothetical benefits of ambiguity that might explain its persistence.
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