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FMR: Functional Meaning Representation & Semantic Parsing Framework

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Projects that uses FMR

mathsolver

What is semantic parsing?

Semantic parsing is the process of mapping a natural language sentence into an intermediate logical form which is a formal representation of its meaning.

The formal representation should be a detailed representation of the complete meaning of the natural language sentence in a fully formal language that:

  • Has a rich ontology of types, properties, and relations.
  • Supports automated reasoning or execution.

Representation languages

Early semantic parsers used highly domain-specific meaning representation languages, with later systems using more extensible languages like Prolog, lambda calculus, lambda dependancy-based compositional semantics (λ-DCS), SQL, Python, Java, and the Alexa Meaning Representation Language. Some work has used more exotic meaning representations, like query graphs or vector representations.

FMR, a formal meaning representation language

Tasks

  • Grammar checkers
  • Dialogue management
  • Question answering
  • Information extraction
  • Machine translation

What can FMR do, a glance overview

// semantic parsing
"五与5.8的和的平方的1.5次方与two的和减去261.712" =>
nf.math.sub(
  nf.math.sum(
    nf.math.pow(
      nf.math.pow(
        nf.math.sum(
          5,
          nf.math.to_number("5.8")
        ),
        2
      ),
      nf.math.to_number("1.5")
    ),
    2
  ),
  nf.math.to_number("261.712")
); // denotation: 1000

// slot filling
"从上海到天津的机票" => nf.flight("上海", "天津");
"到重庆,明天,从北京" => nf.flight("北京", "重庆");
"到上海去" => nf.flight(null, "上海");

References