Talking about trees and truth-conditions

We present Logical Description Grammar (LDG), a model of grammar and the syntax-semantics interface based on descriptions in elementary logic. A description may simultaneously describe the syntactic structure and the semantics of a natural language expression, i.e., the describing logic talks about the trees and about the truth-conditions of the language described. Logical Description Grammars offer a natural way of dealing with underspecification in natural language syntax and semantics. If a logical description (up to isomorphism) has exactly one tree plus truth-conditions as a model, it completely specifies that grammatical object. More common is the situation, corresponding to underspecification, in which there is more than one model. A situation in which there are no models corresponds to an ungrammatical input.

A new problem of descriptive power

No abstract available

Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure

As machine learning systems move from computer-science laboratories into the open world, their accountability becomes a high priority problem. Accountability requires deep understanding of system behavior and its failures. Current evaluation methods such as single-score error metrics and confusion matrices provide aggregate views of system performance that hide important shortcomings. Understanding details about failures is important for identifying pathways for refinement, communicating the reliability of systems in different settings, and for specifying appropriate human oversight and engagement. Characterization of failures and shortcomings is particularly complex for systems composed of multiple machine learned components. For such systems, existing evaluation methods have limited expressiveness in describing and explaining the relationship among input content, the internal states of system components, and final output quality. We present Pandora, a set of hybrid human-machine methods and tools for describing and explaining system failures. Pandora leverages both human and system-generated observations to summarize conditions of system malfunction with respect to the input content and system architecture. We share results of a case study with a machine learning pipeline for image captioning that show how detailed performance views can be beneficial for analysis and debugging

Incremental Interpretation: Applications, Theory, and Relationship to Dynamic Semantics

Why should computers interpret language incrementally? In recent years psycholinguistic evidence for incremental interpretation has become more and more compelling, suggesting that humans perform semantic interpretation before constituent boundaries, possibly word by word. However, possible computational applications have received less attention. In this paper we consider various potential applications, in particular graphical interaction and dialogue. We then review the theoretical and computational tools available for mapping from fragments of sentences to fully scoped semantic representations. Finally, we tease apart the relationship between dynamic semantics and incremental interpretation.Comment: Procs. of COLING 94, LaTeX (2.09 preferred), 8 page

Conceptual thinking in Hegel’s Science of logic

Filozofia analityczna po logicyzmie Fregego i atomizmie logicznym Russella odziedziczyła szereg założeń związanych z istnieniem rodzajowej dziedziny bytów indywidualnych, których tożsamość i elementarne określenia już mamy zdefiniowane. Te „indywidua” istnieją tylko w idealnych „światach możliwych” i nie są niczym innym jak zbiorami posiadającymi strukturę bądź czystymi zbiorami matematycznymi. W przeciwieństwie do takich czysto abstrakcyjnych modeli, Hegel analizuje rolę pojęciowych rozróżnień i odpowiednich brakujących inferencji w rzeczywistym świecie. Tutaj wszystkie obiekty są przestrzennie i czasowo skończone. Nawet jeśli rzeczywiste rzeczy poruszają się zgodnie z pewnymi formami, są tylko momentami w całościowym procesie. Wszelako, formy te nie są przedmiotami bezpośredniej, empirycznej obserwacji, lecz zakładają udane i powtarzalne działania i akty mowy. W rezultacie żadna semantyka odnoszącej się do świata referencji nie może obyć się bez kategorii Heglowskich, które wykraczają daleko poza narzędzia opartej wyłącznie na relacjach logiki matematycznej

Folk moral relativism

It has often been suggested that people’s ordinary folk understanding of morality involves a rejection of moral relativism and a belief in objective moral truths. The results of six studies call this claim into question. Participants did offer apparently objectivist intuitions when confronted with questions about individuals from their own culture, but they offered increasingly relativist intuitions as they were confronted with questions about individuals from increasingly different cultures or ways of life. In light of these data, the authors hypothesize that people do not have a fixed commitment to moral objectivism but instead tend to adopt different views depending on the degree to which they consider radically different perspectives on moral questions. [NOTE: This is a reprint of Sarkissian et al 2011

Husserl, Dummett, and the linguistic turn

Michael Dummett famously holds that the “philosophy of thought” must proceed via the philosophy of language, since that is the only way to preserve the objectivity of thoughts while avoiding commitments to “mythological,” Platonic entities. Central to Dummett’s case is his thesis that all thought contents are linguistically expressible. In this paper, I will (a) argue that making the linguistic turn is neither necessary nor sufficient to avoid the problems of psychologism, (b) discuss Wayne Martin’s argument that not all thought-contents are linguistically communicable, and (c) present another, stronger argument, derived from Husserl’s early account of fulfillment, that establishes the same conclusion