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Linglib.Phenomena.Dialogue.Studies.Ginzburg2012

Ginzburg (2012): The Interactive Stance #

@cite{ginzburg-2012}

Key empirical claims from @cite{ginzburg-2012} formalized against the KOS framework and verified with the existing DGB/TIS/conversational-rule machinery.

Claims Formalized #

  1. Non-sentential utterances (Ch. 5): bare fragments ("Paris.") are resolved via QUD — the question on QUD determines the fragment's propositional content.
  2. Assertion–QUD coupling (Ch. 4): asserting p pushes About(p) onto QUD; the addressee's acceptance resolves it.
  3. Grounding asymmetry (Ch. 4): the speaker's DGB and addressee's DGB evolve differently — only acceptance synchronizes them.
  4. Self-repair (Ch. 7): disfluencies are modeled via TurnUnderConstr in the private state.
  5. Genre relevance (Ch. 4): initiating moves must be relevant to the conversational genre.
  6. NSU taxonomy (Ch. 7, Tables 7.3–7.4): 15 empirical NSU classes from BNC corpus + 4 functional groupings.
  7. Grounding protocol (Ch. 6): LocProp integration branches on cparam resolution — grounding vs CRification.
  8. End-to-end chain (§10): DialogueSign → LocProp → integration → DGB update, with non-resolve-cond verification.

Non-Sentential Utterances #

@cite{ginzburg-2012} Ch. 1 (p. 2) cites estimates that ~30% of utterances are non-sentential (de Waijer 2001); the BNC corpus study in Ch. 7 (§7.2.2) finds 1,299 NSUs in 14,315 sentences (~9%). Their interpretation depends on the QUD — the same fragment "Paris" means different things depending on what question is under discussion:

QUD: "Where's Bo?" → "Paris" = "Bo is in Paris" QUD: "What's the capital of France?" → "Paris" = "Paris is the capital"

The key mechanism: the QUD's question structure determines which argument slot the fragment fills. This connects Phenomena/Ellipsis/FragmentAnswers.lean to the KOS framework.

An NSU resolution datum: a fragment interpreted relative to a QUD.

  • qud : String

    The question under discussion

  • fragment : String

    The non-sentential utterance

  • resolution : String

    The full propositional content derived from QUD + fragment

  • source : String

    Source (chapter/page in Ginzburg 2012)

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      "Where's Bo?" / "Paris" → "Bo is in Paris".

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        "Who called?" / "Bo" → "Bo called".

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          "What did Bo eat?" / "A sandwich" → "Bo ate a sandwich".

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            Bare "yes"/"no" as polar answer.

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                All NSU examples have non-empty resolutions.

                The Full Inquiry Cycle #

                @cite{ginzburg-2012} Ch. 4 (p. 95, ex. 66): the canonical dialogue pattern.

                A(1): "Is Bo here?" — Ask: pushes q onto QUD B(1): "Bo is here." — Assert: adds p to FACTS, pushes About(p), downdates A(2): accepts — Accept: adds p to own FACTS

                We verify that:

                1. After Ask, QUD is non-empty
                2. After Assert (with QUD push), the original question is resolved
                3. After Accept, the fact appears in both participants' views

                After Accept, the fact appears twice (speaker's assert + addressee's accept).

                Speaker vs Addressee DGBs #

                @cite{ginzburg-2012} Ch. 4: each participant maintains their own DGB. After A asserts p, A's DGB has p in FACTS. B's DGB does NOT have p in FACTS until B explicitly accepts. This models the difference between assertion and mutual acceptance.

                Disfluencies and Self-Repair #

                @cite{ginzburg-2012} Ch. 7: self-repairs ("I went to the — to the store") are modeled via TurnUnderConstr. The speaker interrupts the current turn, revises it, and continues. The TuC tracks the partial content so that the repair can target the right constituent.

                We model a simple self-repair: "I saw the, uh, the manager."

                A TuC mid-repair: speaker has said "I saw the" and is about to correct.

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                  The TuC tracks partial content before repair.

                  Genre Constraints on Moves #

                  @cite{ginzburg-2012} §4.6 (pp. 101–110): genres constrain which moves are felicitous. In a bakery transaction, asking about the weather is infelicitous (though not ungrammatical); in casual chat, it's fine.

                  We verify that genre constraints correctly filter moves.

                  A bakery genre: only questions about baked goods are relevant.

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                    Bridge to Fragment Answer Data #

                    @cite{ginzburg-2012} Ch. 5 subsumes the fragment answer phenomenon: bare fragments are NSUs resolved via QUD. The FragmentDatum data from Phenomena/Ellipsis/FragmentAnswers.lean are instances of NSU resolution where the QUD is an explicit wh-question.

                    Fragment answers are NSUs: the question context provides the QUD, and the fragment is the non-sentential utterance.

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                      The subject fragment answer maps to an NSU datum.

                      NSU Classification #

                      @cite{ginzburg-2012} Ch. 7 (§7.2, Tables 7.3–7.4): empirical taxonomy of non-sentential utterances based on a BNC corpus study (Fernández 2006). 200 speaker-turns from 54 BNC files; 14,315 sentences; 1,299 NSUs found, of which 1,283 (98.9%) were classified.

                      Table 7.3 gives 15 empirical classes ordered by frequency. Table 7.4 groups them into 4 functional categories: positive feedback, answers, metacommunicative queries, extension moves.

                      The 15 NSU classes from @cite{ginzburg-2012} Table 7.3 (p. 221). Ordered by frequency in the BNC sub-corpus.

                      • plainAcknowledgement : NSUClass

                        "mmh", "uh-huh" — acknowledges preceding utterance (599)

                      • shortAnswer : NSUClass

                        "Bo" — fills argument slot in MaxQUD (188)

                      • affirmativeAnswer : NSUClass

                        "Yes" — positive answer to polar query (105)

                      • repeatedAcknowledgement : NSUClass

                        "Bo, hmm" — acknowledgement with repetition (86)

                      • clarificationEllipsis : NSUClass

                        "Bo?" — clarification ellipsis (79)

                      • rejection : NSUClass

                        "No" — negative answer to polar query / assertion (49)

                      • factiveModifier : NSUClass

                        "Great!" — factive modifier (27)

                      • repeatedAffirmativeAnswer : NSUClass

                        "Bo, yes" — affirmative with repetition (26)

                      • helpfulRejection : NSUClass

                        "No, Max" — rejection with helpful alternative (24)

                      • sluice : NSUClass

                        "Who?" — bare wh-phrase requesting elaboration (24)

                      • checkQuestion : NSUClass

                        "Okay?" — rising intonation check (22)

                      • filler : NSUClass

                        "uh", "well" — hesitation / floor-holding (18)

                      • bareModifierPhrase : NSUClass

                        "Yesterday" — bare modifier phrase (15)

                      • propositionalModifier : NSUClass

                        "Maybe" — propositional modifier (11)

                      • conjunctionFragment : NSUClass

                        "And Max" — conjunction + fragment (10)

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                          Functional grouping from @cite{ginzburg-2012} Tables 7.1–7.2 (pp. 219–220). The per-group counts are computed from the per-class frequencies in Table 7.3.

                          • positiveFeedback : NSUFunction

                            Positive feedback: plain + repeated acknowledgement (599 + 86 = 685)

                          • answer : NSUFunction

                            Answers: short, affirmative, rejection, repeated aff., helpful rej., prop. modifier (403)

                          • metacommunicativeQuery : NSUFunction

                            Metacommunicative queries: CE, sluice, check question, filler (79 + 24 + 22 + 18 = 143). Note: the Sluice class is ambiguous between a metacommunicative "reprise sluice" reading (the more common one per §7.2.1) and a "direct sluice" reading that functions as an information query. The BNC data (Table 7.3) does not split the 24 sluice instances; we follow the primary classification (Tables 7.1–7.2) in placing sluice here. Direct sluice receives separate grammatical treatment in §7.8 and the Ch. 9 summary.

                          • extensionMove : NSUFunction

                            Extension moves: factive modifier, bare modifier, conj+frag (27 + 15 + 10 = 52)

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                              Classify an NSU class into its functional group (Tables 7.1–7.2).

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                                All 15 NSU classes (Table 7.3).

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                                  theorem Phenomena.Dialogue.Studies.Ginzburg2012.functional_groups_sum_to_total :
                                  have groups := List.map (fun (c : NSUClass) => (c.toFunction, c.frequency)) allNSUClasses; have pf := (List.map (fun (x : NSUFunction × ) => x.2) (List.filter (fun (x : NSUFunction × ) => x.1 == NSUFunction.positiveFeedback) groups)).sum; have ans := (List.map (fun (x : NSUFunction × ) => x.2) (List.filter (fun (x : NSUFunction × ) => x.1 == NSUFunction.answer) groups)).sum; have mcq := (List.map (fun (x : NSUFunction × ) => x.2) (List.filter (fun (x : NSUFunction × ) => x.1 == NSUFunction.metacommunicativeQuery) groups)).sum; have ext := (List.map (fun (x : NSUFunction × ) => x.2) (List.filter (fun (x : NSUFunction × ) => x.1 == NSUFunction.extensionMove) groups)).sum; pf = 685 ans = 403 mcq = 143 ext = 52 pf + ans + mcq + ext = 1283

                                  Functional group frequencies sum to the total (1283).

                                  Clarification Request Taxonomy #

                                  @cite{ginzburg-2012} Ch. 6 (§6.2.1): 8 forms of clarification request, each compatible with up to 4 reading types.

                                  The 8 CR forms from @cite{ginzburg-2012} Ch. 6 §6.2.1.

                                  • wot : CRForm

                                    "Wot?" / "What?" — most general CR

                                  • literalReprise : CRForm

                                    Literal reprise: exact echo with rising intonation ("Bo?")

                                  • whSubstituted : CRForm

                                    Wh-substituted reprise: echo with wh-word ("Bo did WHAT?")

                                  • repriseSluice : CRForm

                                    Reprise sluice: bare wh-word after antecedent ("Who?")

                                  • repriseFragment : CRForm

                                    Reprise fragment: bare constituent echo ("Bo?")

                                  • gap : CRForm

                                    Gap: reprise with a gap ("Did __ leave?")

                                  • fillerCR : CRForm

                                    Filler: "Huh?"

                                  • explicit : CRForm

                                    Explicit: metalinguistic ("What do you mean 'finagle'?")

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                                      The 4 CR reading types from @cite{ginzburg-2012} Ch. 6 §6.2.1.

                                      • clausalConfirmation : CRReading

                                        "Are you asking/saying that p?" — confirms propositional content

                                      • intendedContent : CRReading

                                        "What do you mean by X?" — requests intended referent/predicate

                                      • repetition : CRReading

                                        "Can you repeat X?" — requests phonological repetition

                                      • correction : CRReading

                                        "Did you say X or Y?" — corrective alternative

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                                          Grounding vs CRification #

                                          @cite{ginzburg-2012} Ch. 6: when "Did Bo leave?" enters Pending, the addressee either grounds it (if they know who "Bo" is) or CRifies it (if "Bo" is unresolved → "Who's Bo?").

                                          We show the branching behavior using integrateLocProp.

                                          End-to-End: DialogueSign → LocProp → Integration → DGB #

                                          @cite{ginzburg-2012}'s architecture connects grammar to dialogue via:

                                          1. A DialogueSign (Ch. 5) with dgb-params, q-params, quest-dom
                                          2. Conversion to a LocProp (Ch. 6) with cparams
                                          3. Integration: grounding (cparams resolved → FACTS) or CRification (cparams unresolved → CR question on QUD)
                                          4. DGB update via conversational rules (Ch. 4)

                                          This section proves the full pipeline for the worked example "Did Jo leave?" — from DialogueSign to final DGB state.

                                          After CRification, QUD has the CR question at the top.

                                          The full chain is consistent: CRification and grounding are exhaustive. Every LocProp either grounds or CRifies — there is no third option.