Modeling Cross-Cultural Pragmatic Inference with Codenames Duet
Omar Shaikh Caleb Ziems William Held Aryan J. Pariani Fred Morstatter Diyi Yang
Pragmatic reference enables efficient interpersonal communication. Prior work
uses simple reference games to test models of pragmatic reasoning, often with
unidentified speakers and listeners. In practice, however, speakers'
sociocultural background shapes their pragmatic assumptions. For example,
readers of this paper assume NLP refers to "Natural Language Processing," and
not "Neuro-linguistic Programming." This work introduces the Cultural Codes
dataset, which operationalizes sociocultural pragmatic inference in a simple
word reference game.
  Cultural Codes is based on the multi-turn collaborative two-player game,
Codenames Duet. Our dataset consists of 794 games with 7,703 turns, distributed
across 153 unique players. Alongside gameplay, we collect information about
players' personalities, values, and demographics. Utilizing theories of
communication and pragmatics, we predict each player's actions via joint
modeling of their sociocultural priors and the game context. Our experiments
show that accounting for background characteristics significantly improves
model performance for tasks related to both clue giving and guessing,
indicating that sociocultural priors play a vital role in gameplay decisions.