<p>Crowdsourced normative ratings have benefited psycholinguistic research considerably. Yet, Modern Standard Arabic (MSA) has scarce word norms. To address this scarcity, the current study developed and validated the Kalimah norms in two experiments. In experiment <InternalRef RefID="Sec8">1</InternalRef>, 803 native Arabic speakers provided age of acquisition (AOA) and concreteness (CNC) ratings for 2,467 MSA words, a subset of which was lexically ambiguous (<i>N</i> = 60). Correlations with 12 Arabic and international norms established the sufficient validity of the Kalimah norms. We also observed variations in the ratings for the distinct meanings of the same word form. In experiment <InternalRef RefID="Sec23">2</InternalRef>, we show that our crowdsourced norms can be used to validate large language model&#xa0;(LLM)-generated norm ratings for MSA words. Based on this, we obtained LLM-generated CNC ratings for an additional set of 30,000 MSA words. We make both the Kalimah norms and LLM-generated CNC ratings freely available for research purposes.</p>

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Kalimah norms: Ratings for 2,467 modern standard Arabic words on two scales

  • Alaa Alzahrani,
  • Wafa Aljuaythin,
  • Hassan Alshumrani,
  • Alaa Mamoun Saleh,
  • Mohamed M. Mostafa

摘要

Crowdsourced normative ratings have benefited psycholinguistic research considerably. Yet, Modern Standard Arabic (MSA) has scarce word norms. To address this scarcity, the current study developed and validated the Kalimah norms in two experiments. In experiment 1, 803 native Arabic speakers provided age of acquisition (AOA) and concreteness (CNC) ratings for 2,467 MSA words, a subset of which was lexically ambiguous (N = 60). Correlations with 12 Arabic and international norms established the sufficient validity of the Kalimah norms. We also observed variations in the ratings for the distinct meanings of the same word form. In experiment 2, we show that our crowdsourced norms can be used to validate large language model (LLM)-generated norm ratings for MSA words. Based on this, we obtained LLM-generated CNC ratings for an additional set of 30,000 MSA words. We make both the Kalimah norms and LLM-generated CNC ratings freely available for research purposes.