The dissertation of Andreas Stolcke is approved: University of ...

CHAPTER 5. PROBABILISTIC ATTRIBUTE GRAMMARS 116VP.h = Vi.h--> X NPVP.g = NP.fVP.h = X.hX --> Vc PX.h = P.h--> VtX.h = Vt.hNotice again the non-traditional (Vc P) chunk, which in this case also happens be a good match for theattribute passing rules. The (Vc P) allows collapsing both the CFG productions and the feature equations ofthe VP expansions for copula and transitive sentences.5.4.2 Syntactic constraints imposed by attributesIt is possible to find cases where the unstructured feature assignments supplied as part of thesamples implicitly favor one phrase structure over another, exhibiting a primitive form of semanticallyinduced syntactic bias. Due to the simplicity of the PAG formalism these interactions are not as pervasive asone might think. Also, purely syntactic contingencies tend to interfere and render the semantically preferredalternative dominant regardless of attributes.Interestingly, the following example of semantic bias is entirely based on the likelihood (data fit)component of the posterior probability, so the phenomenon is not dependent on the bias embodied in the priordistribution.We start with a set of sample sentences exhibiting three types of sentence phrase structure. (Forbrevity, we give one sample sentence for each, but the example would also go through if each structure hadan associated set of samples instead.)a circle touches a squarea circle is below a squarebelow a square is a circleAssume that initial merging and chunking has resulted in the traditional NP and PP phrase categories.The baseline grammar for the example is now as follows; the samples corresponding to the rules are listed forconvenience.S --> NP Vt NPS.tr = NP(1).fS.rel = Vt.gS.lm = NP(2).fS --> NP Vi PPS.tr = NP.fS.rel = PP.gS.lm = PP.hS --> PP Vi NPS.tr = NP.fS.rel = PP.gS.lm = PP.h(a circle touches a square)(a circle is below a square)(below a square is a circle)