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Inference Generation

Inference Generation. Last updated 4/17/00 – Please be sensitive to this update date if you are reading this on the Internet – I almost certainly will add slides to this presentation as the weeks go on! Newer slides appear toward end (not sprinkled throughout!). “Inference” – some definitions.

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Inference Generation

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  1. Inference Generation Last updated 4/17/00 – Please be sensitive to this update date if you are reading this on the Internet – I almost certainly will add slides to this presentation as the weeks go on! Newer slides appear toward end (not sprinkled throughout!)

  2. “Inference” – some definitions • An inference is any conclusion that one is reasonably entitled to draw from a sentence or utterance. • An inference is the process of moving from (possibly provisional) acceptance of some propositions, to acceptance of others. The goal of logic and of classical epistemology (study of knowledge) is to codify kinds of inference, and to provide principles for separating good from bad inferences. • An inference isa meaning or a conclusion that is somehow more than the literal interpretation of an utterance.

  3. Implicature • Sometimes we can think of an inference as “what is implied” by the “saying of something.” Another word for this is implication. A fancy word linguists and philosophers of language use is implicature.

  4. “Meaning” is a function of: what is said meaning implicature context Unless it is a straight “semantic” inference” – then context not a factor in generation of meaning

  5. Examples of what the heck we are talking about

  6. What I don’t mean by “meaning” • By “meaning,” I do not mean to refer to, e.g., existential meaning – “Life has no meaning” or “My career means nothing!” or “Dark clouds mean rain.”

  7. What I mean by “meaning” Rather, I am simply referring to more pedestrian – but actually quite complex – meaning such as: • “The meaning of the word dog is any member of the large and varied group of domesticated animals that scientists capture under the label Canis familiaris.” • “When he said that the car was a dog, he didn’t mean that it was a member of Canis familiaris, but rather that it was a crummy vehicle.”

  8. Inference revisited • Remember, an implication or implicature (the 3 terms are more or less interchangeable) is ameaning or a conclusion that is somehow more than the literal interpretation of an utterance.

  9. The way to decompose problems of inference Simply break it down into: • What is literally SAID • What is MEANT Often, what is MEANT is more than what is SAID. Sometimes not. When it is, we speak of “pragmatic inference.” When it is not, we speak of “semantic inference.”

  10. Lordy, this sounds complicated.But it’s not.Let’s look at some examples of what the heck I’m talking about.

  11. Examples of inferences

  12. Semantic inference – don’t need a context (What is SAID is in quotes; what is semantically inferred follows the arrow) • “John is a bachelor”  John is a man. • “Eliza plays the fiddle”  Someone plays a musical instrument. • “Mary owns three canaries”  Mary owns a canary.

  13. Semantic inference • “All men are mortal” • “Socrates is a man”  Therefore, Socrates is mortal.

  14. In linguistics (and in this class), we are concerned primarily with pragmatic inferences – this is the stuff linguists study and is the source of so much linguistic mischief in the world. • From here on out, we will only be concerned with pragmatic inferences or implicatures

  15. Pragmatic inference • A professor was asked by his student for a recommendation to Harvard Law School. In the recommendation form, all the professor wrote was: • “Mr. xyz was very punctual and attended all classes. Best wishes, Professor Tinhorn.” • What is literally said? • What is implied? • How does context seem to figure in the generation of this inference?

  16. Concept (signifié) Sound image (signifiant) The linguistic sign, as described by Ferdinand de Saussure (1857-1913) in the Cours de linguistique générale.

  17. The Cooperative Principle Quantity • Make your contribution as informative as is required for the current purposes of the exchange. • Do not make your contribution more informative than is required. Quality • Try to make your contribution one that is true. In other words: 1. Don’t say things you know are false. 2. Don’t say things for which you lack adequate evidence. Relation • Be relevant. Manner • Be perspicuous [L. persicuus “transparent”] 1. Avoid obscurity of expression 2. Avoid ambiguity 3. Be brief 4. Be orderly

  18. A: Let’s get the kid’s something.B: Ok, but I veto I-C-E-C-R-E-A-M • Inference (implication)? • Speaker B conveys to A by inference that B would rather not have ice-cream mentioned directly in the presence of some of the children. • How is this inference generated? • Flouting of Manner

  19. Nigel has 14 children. • Inference (implication)? • Nigel has only 14 children, and no more. But this sentence would be compatible with a situation in which, in fact, Nigel has 19 children. • How is this inference generated? • The assumption that the Maxim of Quantity is observed. If he has more children, then the Maxim of Quantity says I will say so!

  20. A: I need a coffee.B: Try the Chat. • Inference (implication)? • The Chat is a place that sells coffee, it is open, and it is nearby (e.g. not in Wisconsin). • How is this inference generated? • The assumption that the Maxims of Quality and Relation are being observed.

  21. A: Can you tell me the time?B: Well, Celis’s class has just let out. • Inference (implication)? • It is implicated that B does not know the exact time, but he thinks that the reporting of Celis’s class being overwill at least help out or provide a partial answer. • How is this inference generated? • By assuming the Maxim of Relation is being observed.

  22. Sentence 1: Open the door.Sentence 2: Walk up to the door, turn the door handle clockwise as it will go, and then pull gently towards you. • Inference (implication) of sentence 2 as opposed to sentence 1? • It is implicated that for whatever reason, it is important that you are aware of the precise steps involved in door opening. • How is this inference generated? • In the sentence (2), the 3rd sub-maxim (be brief) of Manner is flouted, but because these details are at a deeper level somehow more relevant.

  23. ?? The Lone Ranger rode off into the sunset and jumped on his horse. • Why is this sentence anomalous? • It is anomalous because it violates the 4th sub-maxim of Manner, namely”Be orderly.” That is, it violates our expectation that events are recounted in the order in which they happened. It is just because participants in converation may be expected to observe the sub-maxim “be orderly” that we have that expectation.

  24. Boy, that John is a real rocket scientist. (said sarcastically) • Inference (implication)? • John is an idiot. • How is this inference generated? • Flouting the Maxim of Quality.

  25. (1) War is war.(2) Either he’ll come our he won’t come (said in appropriately irritated and tired voice)(3) If he does it, he does it. • What are the inferences associated with these sentences? • They all come about by flouting the Maxim of _____ • Quantity!

  26. (1) A: That guy Celis is a real pain in the neck, isn’t he!B: Uh, lovely weather for July, isn’t it? • What is the inference - viz., what is being communicated by B’s sentence? • This inference comes about by flouting the Maxim of _____ • Relation!

  27. (1) Miss Bartoli produced a series of sounds corresponding closely to the score of an aria from The Barber of Seville.vs.(2) Miss Bartoli sang an aria from The Barber of Seville. • What is the inference - viz., what is being communicated by the first sentence? • This inference comes about by flouting the Maxim of _____ • Manner! (be brief and avoid obscurity of expression)

  28. literal meaning - The literal meaning of a sentence is the conditions in the world which would have to be met for the sentence to be true. Thus the literal meaning of a sentence is simply a list of conditions in which that sentence is true, also known as “truth conditions.” For the sentence Snow is white to be true, you have to have a world in which snow is indeed white. If, in your world, all snow is neon green, then the sentence Snow is white is false. inference[L. inferre ‘to bring, carry’] - Something derived from reasoning. Sometimes this process of reasoning is very subtle and even unconscious. Thus, if I state while you are driving, “There is a sharp curve ahead,” you will probably infer - quickly and unconsciously - that I intend for you to modify your driving in some way. But this intention is not part of the literal meaning of the sentence. It is derived via some process of inference. More specifically, it is derived via some process of “conversational implicature.” conversational implicature - An inference (viz., not the literal meaning of the utterance) that arises through a “flouting” of one or more of the Maxims of Conversation that are listed under the Cooperative Principle. Strictly speaking, for an inference to be considered a species of conversational implicature, it must pass certain linguistic-pragmatic tests. Cooperative Principle - The principles or “maxims” of reasonable and cooperative conversation. rhetoric - The art of using language so as to persuade or influence others. Much of understanding how language is used for influence lies in understanding the inferences generated by certain words or sentences, and how these inferences come about.

  29. The notion of convention(alization) • Las señoras de pollera (cholas) of La Paz, Bolivia bowlers derived from aristrocratic fashions of 16th century Spain. • West-Indian dancehall cigarette lighter drive-bys (and the entire phenomenon of dancehall, as opposed to reggae).

  30. Convention • A convention is a regularity in behavior to which, in a given situation, almost everyone within a population conforms and expects almost everyone else to conform – moreovever, almost everyone prefers this state of affairs to an alternative. • Frequently – and this is the case with, e.g., the bowler hats and cholas you just say, the original meaning or rationale behind the convention becomes either unconscious or forgotten – or entirely irrelevant.

  31. Convention • If the process is pushed far enough, the connection can even become completely arbitrary in the sense that Monsieur Saussure spoke about. • For example, the connection for Bolivian women between bowler hats and aristocratic 16th century Spain probably has largely been lost. It is simply a cultural dress convention for women of this society to wear bowler hats.

  32. Convention • Great examples of conventions with varying degrees of arbitrariness are idioms in English, e.g. “to rain cats and dogs,” “cup of tea,” “pull my leg.” • The interesting thing about the way languages change througout their history is that they don’t just generally become completely conventional overnight. • Next week we will look at some empirical procedures linguists have effectively used to differentiate the degree to which something is completely conventional (e.g., meaning of an expression doesn’t have to be thought out, even if unconsciously, via, e.g., the Coop Principle) or not conventional at all (so meaning is derived through context and calculation via, e.g., the Coop Principle).

  33. Language Game – An alternative way of explaining where inferences come from • Language games – An internal and subconscious set of rules we all carry around based on our having had experience in the world – these rules being associated with particular activity types.

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