From 45c932f9cb26f0144f3f5ce26b64d60e44f9b854 Mon Sep 17 00:00:00 2001 From: Patrick Simianer Date: Thu, 25 Apr 2013 10:29:57 +0200 Subject: added Gesa's parse match feature function --- decoder/ff_parse_match.cc | 218 ++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 218 insertions(+) create mode 100644 decoder/ff_parse_match.cc (limited to 'decoder/ff_parse_match.cc') diff --git a/decoder/ff_parse_match.cc b/decoder/ff_parse_match.cc new file mode 100644 index 00000000..ed556b91 --- /dev/null +++ b/decoder/ff_parse_match.cc @@ -0,0 +1,218 @@ +#include "ff_parse_match.h" + +#include +#include +#include + +#include "sentence_metadata.h" +#include "array2d.h" +#include "filelib.h" + +using namespace std; + +// implements the parse match features as described in Vilar et al. (2008) +// source trees must be represented in Penn Treebank format, e.g. +// (S (NP John) (VP (V left))) + +struct ParseMatchFeaturesImpl { + ParseMatchFeaturesImpl(const string& param) { + if (param.compare("") != 0) { + char score_param = (char) param[0]; + switch(score_param) { + case 'b': + scoring_method = 0; + break; + case 'l': + scoring_method = 1; + break; + case 'e': + scoring_method = 2; + break; + case 'r': + scoring_method = 3; + break; + default: + scoring_method = 0; + } + } + else { + scoring_method = 0; + } + } + + void InitializeGrids(const string& tree, unsigned src_len) { + assert(tree.size() > 0); + //fids_cat.clear(); + fids_ef.clear(); + src_tree.clear(); + //fids_cat.resize(src_len, src_len + 1); + fids_ef.resize(src_len, src_len + 1); + src_tree.resize(src_len, src_len + 1, TD::Convert("XX")); + ParseTreeString(tree, src_len); + } + + void ParseTreeString(const string& tree, unsigned src_len) { + //cerr << "TREE: " << tree << endl; + src_sent_len = src_len; + stack > stk; // first = i, second = category + pair cur_cat; cur_cat.first = -1; + unsigned i = 0; + unsigned p = 0; + while(p < tree.size()) { + const char cur = tree[p]; + if (cur == '(') { + stk.push(cur_cat); + ++p; + unsigned k = p + 1; + while (k < tree.size() && tree[k] != ' ') { ++k; } + cur_cat.first = i; + cur_cat.second = TD::Convert(tree.substr(p, k - p)); + // cerr << "NT: '" << tree.substr(p, k-p) << "' (i=" << i << ")\n"; + p = k + 1; + } else if (cur == ')') { + unsigned k = p; + while (k < tree.size() && tree[k] == ')') { ++k; } + const unsigned num_closes = k - p; + for (unsigned ci = 0; ci < num_closes; ++ci) { + // cur_cat.second spans from cur_cat.first to i + // cerr << TD::Convert(cur_cat.second) << " from " << cur_cat.first << " to " << i << endl; + // NOTE: unary rule chains end up being labeled with the top-most category + src_tree(cur_cat.first, i) = cur_cat.second; + cur_cat = stk.top(); + stk.pop(); + } + p = k; + while (p < tree.size() && (tree[p] == ' ' || tree[p] == '\t')) { ++p; } + } else if (cur == ' ' || cur == '\t') { + cerr << "Unexpected whitespace in: " << tree << endl; + abort(); + } else { // terminal symbol + unsigned k = p + 1; + do { + while (k < tree.size() && tree[k] != ')' && tree[k] != ' ') { ++k; } + // cerr << "TERM: '" << tree.substr(p, k-p) << "' (i=" << i << ")\n"; + ++i; + assert(i <= src_len); + while (k < tree.size() && tree[k] == ' ') { ++k; } + p = k; + } while (p < tree.size() && tree[p] != ')'); + } + //cerr << "i=" << i << " src_len=" << src_len << endl; + } + //cerr << "i=" << i << " src_len=" << src_len << endl; + assert(i == src_len); // make sure tree specified in src_tree is + // the same length as the source sentence + } + + int FireFeatures(const TRule& rule, const int i, const int j, int* ants, SparseVector* feats) { + //cerr << "fire features: " << rule.AsString() << " for " << i << "," << j << endl; + //cerr << rule << endl; + //cerr << "span: " << i << " " << j << endl; + const WordID lhs = src_tree(i,j); + int fid_ef = FD::Convert("PM"); + int min_dist; // minimal distance to next syntactic constituent of this rule's LHS + int summed_min_dists; // minimal distances of LHS and NTs summed up + if (TD::Convert(lhs).compare("XX") != 0) + min_dist= 0; + // compute the distance to the next syntactical constituent + else { + int ok = 0; + for (unsigned int k = 1; k < (j - i); k++) { + min_dist = k; + for (unsigned int l = 0; l <= k; l++) { + // check if adding k words to the rule span will + // lead to a syntactical constituent + int l_add = i-l; + int r_add = j+(k-l); + //cerr << "Adding: " << l_add << " " << r_add << endl; + if ((l_add < src_tree.width() && r_add < src_tree.height()) && (TD::Convert(src_tree(l_add, r_add)).compare("XX") != 0)) { + //cerr << TD::Convert(src_tree(i-l,j+(k-l))) << endl; + //cerr << "span_add: " << l_add << " " << r_add << endl; + ok = 1; + break; + } + // check if removing k words from the rule span will + // lead to a syntactical constituent + else { + //cerr << "Hilfe...!" << endl; + int l_rem= i+l; + int r_rem = j-(k-l); + //cerr << "Removing: " << l_rem << " " << r_rem << endl; + if ((l_rem < src_tree.width() && r_rem < src_tree.height()) && TD::Convert(src_tree(l_rem, r_rem)).compare("XX") != 0) { + //cerr << TD::Convert(src_tree(i+l,j-(k-l))) << endl; + //cerr << "span_rem: " << l_rem << " " << r_rem << endl; + ok = 1; + break; + } + } + } + if (ok) break; + } + } + summed_min_dists = min_dist; + //cerr << min_dist << endl; + unsigned ntc = 0; + for (unsigned k = 0; k < rule.f_.size(); ++k) { + int fj = rule.f_[k]; + if (fj <= 0) + summed_min_dists += ants[ntc++]; + } + switch(scoring_method) { + case 0: + // binary scoring + feats->set_value(fid_ef, (summed_min_dists == 0)); + break; + // CHECK: for the remaining scoring methods, the question remains if + // min_dist or summed_min_dists should be used + case 1: + // linear scoring + feats->set_value(fid_ef, 1.0/(min_dist+1)); + break; + case 2: + // exponential scoring + feats->set_value(fid_ef, 1.0/exp(min_dist)); + break; + case 3: + // relative scoring + feats->set_value(fid_ef, (j-i)/((j-i) + min_dist)); + break; + default: + // binary scoring in case nothing is defined + feats->set_value(fid_ef, (summed_min_dists == 0)); + } + return min_dist; + } + + Array2D src_tree; // src_tree(i,j) NT = type + unsigned int src_sent_len; + mutable Array2D > fids_ef; // fires for fully lexicalized + int scoring_method; +}; + +ParseMatchFeatures::ParseMatchFeatures(const string& param) : + FeatureFunction(sizeof(WordID)) { + impl = new ParseMatchFeaturesImpl(param); +} + +ParseMatchFeatures::~ParseMatchFeatures() { + delete impl; + impl = NULL; +} + +void ParseMatchFeatures::TraversalFeaturesImpl(const SentenceMetadata& smeta, + const Hypergraph::Edge& edge, + const vector& ant_contexts, + SparseVector* features, + SparseVector* estimated_features, + void* context) const { + int ants[8]; + for (unsigned i = 0; i < ant_contexts.size(); ++i) + ants[i] = *static_cast(ant_contexts[i]); + + *static_cast(context) = + impl->FireFeatures(*edge.rule_, edge.i_, edge.j_, ants, features); +} + +void ParseMatchFeatures::PrepareForInput(const SentenceMetadata& smeta) { + impl->InitializeGrids(smeta.GetSGMLValue("src_tree"), smeta.GetSourceLength()); +} -- cgit v1.2.3