Lesk Algorithm (1983) › The Dictionary Dependency

The algorithm's effectiveness hinged entirely on the quality and coverage of the dictionary being used. Lesk's original experiments relied on machine-readable dictionaries that were just becoming available in the early 1980s.digitized versions of printed reference works like the Oxford English Dictionary or Merriam-Webster. These resources varied dramatically in their suitability for computational use. Some provided rich, verbose definitions with many content words; others offered terse, minimal definitions that left little surface form for overlap detection. The granularity of sense distinctions mattered too: dictionaries with very fine-grained sense divisions (distinguishing, for instance, between "bank" as a building versus "bank" as an institution) made disambiguation harder by fragmenting definitional overlap across multiple similar senses.

The choice of dictionary fundamentally shaped what the algorithm could achieve. A financial dictionary would provide excellent disambiguation for domain-specific text but fail on general language. A children's dictionary with simplified definitions might lack the technical vocabulary needed for scientific texts but perform well on informal writing. No single dictionary served all purposes, yet creating domain-specific or application-specific dictionaries required substantial lexicographic effort. This tension between generality and specificity reflected a broader challenge in early NLP: resources designed for human readers often proved awkward for computational processing, while resources designed computationally (like early semantic networks) lacked the coverage and nuance of human-curated references.