PhD/Postdoc project descriptions for the research program

Between Logic and Common Sense: The Formal Semantics of Words

supported by an NWO Vici grant

February 2010

Principal investigator:   Yoad Winter

Expected starting date for all projects:   1 October 2010 (negotiable)



Project 1: PhD/Postdoc project in Formal Semantics – Logic and the semantics of concepts

Remark: All cross-references below refer to the general program:

The project will model the effects of lexical meanings on logical meanings, employing theories of concepts in cognitive psychology, especially Prototype Theory. An important test case is described below, following work done in Kerem, Friedmann and Winter (2009). Many relational expressions are assumed to have representations as in (11), with defeasible and indefeasible restrictions on their meaning:

(17)  Functionality:     pinch, give birth to, kick

        Transitivity:        equal,contain, consecutive

        Symmetry:        overlap, similar, parallel

        Asymmetry:       stand on, follow

The Maximal Typicality Hypothesis (section 4.2) assumes that such restrictions interface logical modules of entailment. Project 1 will test and generalize this hypothesis to other domains of formal semantics besides reciprocity and relational meanings.

Research goal:

Use and generalize the Maximal Typicality Hypothesis for specifying the logical structure in the common sense meaning of relational and other expressions and its interactions with logical meanings.


The project will involve three tasks:

1. Using the correspondence principle (section 4.3) for elaborating the logical structure of feature-based representations of relational (11) and other expressions.

2. Explaining the interactions of these representations with the logical expressions like reciprocals (each other), using the Maximal Typicality Hypothesis and previous work on reciprocals (Dalrymple et al. 1998, Winter 2001b, Sabato and Winter 2005, Kerem, Friedmann and Winter 2009).

3. Using the plug-in principle on pragmatic effects with reciprocals in the formal pragmatics of reciprocals and other logical expressions (Roberts 1987, Schwarzschild 1996).

Contribution to the program:

By modeling the interactions between lexical semantics and logical semantics, project 1 will examine the Maximal Typicality Hypothesis of Content Sensitive Formal Semantics in an important test case.  


Project 2: PhD/Postdoc project in Psycholinguistics – Typicality effects with logical expressions

Remark: All cross-references below refer to the general program:

According to the main hypothesis (section 3) and its elaboration in the Maximal Typicality Hypothesis (section 4.2), entailment involves semantic manipulation of feature-based representations of common sense meanings. An expected result is that there should be a clear reflection of typicality effects in the logical interpretation of sentences. Project 2 will experimentally investigate this expectation for typicality of relational expressions appearing within reciprocal sentences, thereby informing the theory developed in project 1. The project will experimentally address three types of data:

-       Typicality effects with relational expressions and their account using feature-based representations.

-       The influence of such effects on semantic judgments about sentences with reciprocal expressions: each other, mutually, one another.

-       The expected parallelism (cf. Maximal Typicality Hypothesis) between this influence and the influence of typicality on the interpretation of modification constructions: red car, red hair, striped apple.

The project will aim to reproduce and systematize results by Kerem, Friedmann and Winter (2009), and to check experimentally further implications of the correspondence between lexical meaning and logical meaning.

Research Goal:

Characterizing experimentally the effects of typicality on the logical interpretation of sentences; comparing such effects reciprocals to parallel effects with modification constructions.


A battery of tests will be developed, following Kerem, Friedmann and Winter (2009), for characterizing typicality effects with various expressions (e.g. transitive verbs). The experiments will be run together with a research assistant. For testing typicality, the project will use standard methods of prototype theory (Smith 1990, Connolly et al. 2007). For instance, in (11) we hypothesize that typical situations with the concept pinch involve only one patient per agent simultaneously. To check this hypothesis, Figures like 4a and 4b will be presented separately to subjects, who will be asked to classify them as appropriate or inappropriate pinching activities. If our hypothesis is correct, we expect subjects to respond positively to both figures, but react more quickly to Figure 4a than to Figure 4b.


Figure 4: typical pinching vs. atypical pinching

        In order to check the hypothesis that typicality affects reciprocal sentences, subjects will be shown sentences with a reciprocal verb phrase (e.g. pinch each other) and will be asked to evaluate them in different situations like Figures 4c and 4d. If our hypothesis about the effects of typicality on reciprocal sentences is correct, two phenomena are expected. First, speakers are expected to classify Figure 4c as a “pinch each other” activity, and do that at least as quickly as with Figure 4d. Second, this tolerance of “missing” pinching relations in Figure 4c is expected to crucially depend on the typicality test for the verb pinch. Thus, tolerance to “missing” pinching relations will be compared to other cases such as know each other (2). It is expected that under time pressure, tolerance to exception in the latter case is significantly lower.[1]

        In order to test the parallelism between different typicality effects on sentential meaning, the results in both tests will be compared to the results by Smith et al. (1988) about modification constructions. The project will examine if the similarity-based model of Smith et al. can be extended to fit the results with reciprocal expressions. If needed, further experiments with modification constructions will be designed and run in order to also evaluate the extended model with modification constructions.

Case study:

A pilot version of the typicality test was run with 53 native Hebrew speakers (Kerem, Friedmann and Winter 2009). The results showed clear typicality effects supporting our hypothesis about many transitive action verbs like pinch, in contrast to other verbs.

Contribution to the program:

By characterizing typicality effects with relational expressions and semantic judgments on reciprocal sentences, project 2 will provide experimental data informing the part of Content Sensitive Formal Semantics developed in project 1. By comparing these results to other experimental data on modification constructions, the project will contribute to the development of the general framework.

Project 3: PhD/Postdoc project in Formal Semantics – Quantification and spatial expressions

Remark: All cross-references below refer to the general program:

A central aim of this program is to lay the foundations for a general theory of the lexical semantic parameters that affect entailment phenomena. Project 3 will concentrate on spatial/mereological relational expressions as in (18), whose effects on entailment go beyond the realm of typicality-based accounts.

(18)  Locative prepositions:        inside, outside, behind

        Directional prepositions: around, to, from

        Dimensional adjectives:      big, far, narrow, fast

        Geometrical relations:        cross, overlap, contain, touch, be disjoint from,

                                                be adjacent to, be parallel to

        Mereological relations:       constitute, comprise, member of

        Group-referring nouns:       group, couple, forest

It was only rarely observed that the common sense effects of spatial/mereological expressions on entailments are as far-reaching as those of other well-appreciated phenomena like generic sentences (Carlson and Pelletier 1995), tense and aspect phenomena (Dowty 1979, Hay et al. 1999, Winter 2006), plurality (Link 1983, Scha 1981, Winter 2001a) and intensionality (Zimmermann 2006).

        Examples (3a-c) above illustrated this claim for the spatial words far and near and plural definite descriptions. The same is true for indefinite descriptions. Suppose that you are in Nevada, driving with a friend, when suddenly your car runs out of gas. Now consider the following sentences that your friend may utter in response to the situation:

(19)  a. We are far from a gas station.                b. We are near a gas station.

The two sentences have different implications for the fate of your journey. While (19b) means that some gas station is nearby, (19a) does not simply mean that some gas station is far away. Rather, (19a) conveys the stronger, unfavorable proposition that all gas stations are far from your location. Thus, in (19b) the indefinite a gas station is existential as expected by traditional treatments, but replacing the relational expression in (19b) by its antonym far from leads to a universal statement (19a). The lexical properties of the main relation in (19) interact with quantificational devices to express a statement about a spatial concept: the location of gas stations.

        Quantificational variability with plural definites is not restricted to locative prepositions, as the following examples with spatial transitive verbs illustrate:

(20) a. Zeeburg contains the industrial zones.

        b. Zeeburg overlaps the industrial zones.

(21) a. Mary circled the lakes.                                              

        b. Mary reached the lakes.

(20a) entails that Zeeburg contains all the industrial zones under discussion. However, for (20b) to be true it is sufficient that one industrial zone overlaps Zeeburg. Similarly, in (21a) the relation circle requires that the path described by Mary's movement surrounds all the lakes, but (21b) can hold if Mary only reached one lake, adjacent to others in a big lake district. Similar effects on logical semantics appear with the other spatial/mereological expressions in (18). The project will adopt the following hypothesis:

Spatial Quantification Hypothesis: Quantificational variability appears in entailments with spatial/mereological relations and in/definite descriptions, because descriptions can function as direct arguments of those relations.

Descriptions are assumed to be arguments of predicates, as in previous analyses of semantic incorporation (Zimmermann 1993, Farkas and de Swart 2003, McNally and Van Geenhoven 2005). The Spatial Quantification Hypothesis is an innovative contribution to these accounts in the realm between logic and common sense meaning. In (3a), the description the lakes, denoting a location, is a direct argument of the spatial relation far from. Universal quantification over lakes follows from the definition of this spatial concept – being far from a location means being far from all its sub-locations. In (3b), existential quantification over lakes follows from the different definition of the spatial concept near – being near a location only requires being near one of its sub-locations. Thus, the in/validity of the entailments in (3c) follows from the Spatial-Quantification Hypothesis, and similarly for examples (19)-(21).

Research goal:

Characterize the lexical meanings of spatial and mereological expressions and the ways they affect entailment modules using the Spatial Quantification Hypothesis.


This PhD/Postdoc project will involve theoretical work, and use questionnaires and linguistic judgments of native speakers to support its claims. The theory developed using the Spatial Quantification Hypothesis will extend the theory of project 1 for spatial relations.

Contribution to the program:  

While it has been previously proposed (Gärdenfors 2000) that models of typicality are related to spatial models, this possibility has not been empirically tested in formal semantics. Project 3 will thus make an important contribution to characterizing effects of common sense meanings on entailments.

Project 4: PhD  project in Computational Linguistics – Formal semantic annotation of textual entailments

Remark: All cross-references below refer to the general program:

The RTE corpus (Dagan et al. 2006), which is the only currently available resource of textual entailments, marks candidate entailments as valid/invalid. However, the RTE corpus makes no indication of the linguistic and informational processes that underlie entailment. This situation is comparable to the situation of statistical parsing prior to the introduction of syntactically annotated corpora like the Penn Treebank (Marcus et al. 1993). In the lack of theoretical conceptions and empirical documentation of the processes that support entailments, current works that attempt to automatically recognize entailment have mostly had to rely on heuristic principles. Some recent works (Bos and Markert 2005, MacCartney and Manning 2007) stress the importance of lexical-logical principles (Van Benthem 1987, Sànchez-Valencia 1991, Fyodorov, Winter and Francez 2003) for models of natural language entailments. However, semantic theory itself currently lacks the core principles and typologies that would comprehensively support this challenge for natural language processing. This project will use the new framework of Content Sensitive Formal Semantics, together with previous results, for analyzing and annotating the entailments of the RTE.

Research Goal:

Develop a version of semantic theory that is suitable for annotating a corpus of textual entailments.


Project 4 will both add data to be modeled by the theory developed in projects 1-3 and be used for testing its applicability for the central challenge of entailment recognition. Entailments from the RTE corpus will be annotated using sound semantic relations with a rigorous interpretation in lexical and formal semantics. The annotation scheme and its theoretical foundations will be developed by a PhD student and the principal investigator. The actual annotation will be performed by two assistants, supervised by the principal investigator and supported by the PhD student.

Pilot studies:

As an initial examination of the feasibility of entailment annotation, the principal investigator examined a pilot of twenty valid entailments, picked at random from the RTE corpus. These entailments were annotated according to a provisional scheme that includes eight semantic categories. Six of the categories that were identified are simple relations like (16.1-4), and two categories are of a higher-level nature, similar to (16.5). Of the 87 relations identified in the 20 entailments, about 90% (78 relations) were of the six simple categories. This suggests the feasibility of an annotation scheme using these eight categories, as well as the feasibility of their automatic acquisition and utilization for improving the recognition of entailments. In a subsequent study (Van Strien 2009), an MA student of the principal investigator, developed an XML scheme for annotating common relations of restrictive modification and apposition in the RTE corpus. Two linguist annotators used this scheme for annotating 200 sentences from the RTE corpus, uncovering these two relations as operational in 55% of the valid entailments and achieving 90% cross-annotator agreement results.

Project 5: PhD/Postdoc  project in Computational Linguistics – Automatic acquisition of textual entailments using semantic corpora

Remark: All cross-references below refer to the general program:

As experience in natural language processing has shown, general machine learning algorithms are useful for acquiring effective linguistic generalizations from annotated corpora about language use (Daelemans and van den Bosch 2005, Lappin and Shieber 2007). In this project, generalizations about acquisition of entailment from linguistic resources will be obtained from the annotated corpus (project 4) by general machine learning techniques.

Research goal:

Use annotated entailments for developing machine learning algorithms that recognize unseen entailments on the basis of lexical/syntactic tools and resources.


The PhD/postdoc researcher will develop a machine learning model that will use the annotated corpus of project 4. The corpus will be used as a training set for the acquisition and utilization of tools and resources (e.g. WordNet, Penn Treebank, OpenCyc) for parsing entailments. The PhD/postdoc researcher will be a specialist in machine learning techniques in corpus-based natural language processing, whose expertise will complement those of the principal investigator.

Synchronization between projects 4 and 5:

Projects 4 and 5 are closely connected. The semantic annotation scheme developed in project 4 will inform the computational model of project 5, and using the semantic annotations on the resources will affect the definition of the annotation scheme in project 4.



[1]An experimental caveat: relational verbs like know are not easily tested using graphic descriptions of situations. However, other relations that are easy to draw (hug, make a speech to) are also expected to show indifference to number of patients or preference for multiple patients. Further, another battery of experiments will also test typicality with verbs like know using textual descriptions of situations.