31.2008, Calls: Cog Sci, Comp Ling, Gen Ling, Psycholing, Semantics/Online

[The LINGUIST List]

LINGUIST List: Vol-31-2008. Thu Jun 18 2020. ISSN: 1069 - 4875.

Subject: 31.2008, Calls: Cog Sci, Comp Ling, Gen Ling, Psycholing, Semantics/Online

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Date: Thu, 18 Jun 2020 10:28:44
From: Daniele Radicioni [daniele.radicioni at unito.it]
Subject: CONcreTEXT, Concreteness in Context: trial data release - @Evalita 2020

 
Full Title: CONcreTEXT, Concreteness in Context: trial data release - @Evalita 2020 
Short Title: CONcreTEXT @Evalita 2020 

Date: 30-Nov-2020 - 03-Dec-2020
Location: Bologna, Italy 
Contact Person: Daniele Radicioni Andrea Ravelli
Meeting Email: concretext2020 at gmail.com
Web Site: https://lablita.github.io/CONcreTEXT/ 

Linguistic Field(s): Cognitive Science; Computational Linguistics; General Linguistics; Psycholinguistics; Semantics 

Call Deadline: 24-Sep-2020 

Meeting Description:

### Task: CONcreTEXT @ EVALITA 2020 ###

NEW: *trial data now available for download*
https://lablita.github.io/CONcreTEXT/

The task CONcreTEXT (CONcreteness in conTEXT) focuses on automatic
concreteness (and conversely, abstractness) recognition. Given a sentence
along with a target word, we ask participants to propose a system able to
assess the concreteness of the target word according to a [1-7] concreteness
scale, where 1 stands for fully abstract (e.g., 'idempotence') and 7 for
maximally concrete (e.g., 'car').

The concreteness score being assigned to the word must be evaluated in
context: the word should not be considered in isolation, but as part of the
given sentence. For example, systems are expected to assign different scores
to the verb 'COVER' in the next two sentences:

- COVER the pot and bring the water to a vigorous boil;
- Your fees and tuition help to COVER the costs of providing these services.

Target words may be either verbs or nouns. The dataset used for this task is
taken from the English-Italian parallel section of The Human Instruction
Dataset, derived from WikiHow instructions
(https://www.kaggle.com/paolop/human-instructions-multilingual-wikihow). The
released dataset will be composed by overall 1,000 sentences (500 Italian
sentences plus 500 English sentences), all annotated with human judgment by
native speakers. 

Participants may decide to participate in either task, or both.


Call for Participation: 

We invite participants to exploit all possible strategies to solve the task,
including (but not limited to) knowledge bases, external training data, word
embeddings, multimodal systems, etc.

Registration is now open, at URL: http://www.evalita.it/2020/taskregistration 

Definition of concreteness: 
Operationally, the very first issue is that it is not straightforward to
define concreteness/abstractness. Provided that more fine grained distinctions
on abstract and concrete word meanings can be drawn, the term 'concrete' has
two main interpretations:

- what is closer to perception (as opposed to what cannot be experienced
directly through the senses);
- what is more specific (as opposed to high-level, abstract).

We are mostly interested in the first aspect, that is perceptually salient
concreteness/abstractness.

Motivation and state of the art: 
Ordinary experience suggests that semantic representation and lexical access
and processing of concepts can be affected by concepts' concrete/abstract
status: concrete meanings, closer to perceptual experience, are acknowledged
to be more quickly and easily delivered in human communication than abstract
meanings. Such kind of information grasps a complex combination of
experiential (e.g., sensory, motor) and strictly linguistic features, such as
verbal associations arising through co-occurrence patterns and syntactic
information. These features make conceptual concreteness/abstractness a
challenging though only marginally explored field, with the notable exception
of some works at the intersection between Computational Linguistics and
Cognitive Science.

The CONcreTEXT task is aimed at investigating how the concreteness information
affects sense selection: different from past research, we are interested in
assessing the concreteness of terms in context rather than in isolation. 

The CONcreTEXT task may be relevant also for the psycho-linguistics community,
where ratings about concreteness, imageability and other features are largely
used as control variables in many experiments. The resulting annotated dataset
itself (for both the Italian and English languages) will be a resource to be
exploited for future researches focused on concreteness in a more contextual,
and thus ecological, setting.




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LINGUIST List: Vol-31-2008	
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