The directory src/main/simple_examples in the tarball contains some example programs to illustrate how to call the library.
See the README file in that directory for details on what does each of the programs.
The most complete program in that directory is sample.cc, which is very similar to the program depicted below, which reads text from stdin, morphologically analyzes it, and processes the obtained results.
Note that depending on the application, the input text could be obtained from a speech recongnition system, or from a XML parser, or from any source suiting the application goals. Similarly, the obtained analysis, instead of being output, could be used in a translation system, or sent to a dialogue control module, etc.
int main() { string text; list<word> lw; list<sentence> ls; string path="/usr/local/share/FreeLing/es/"; // create analyzers tokenizer tk(path+"tokenizer.dat"); splitter sp(path+"splitter.dat"); // morphological analysis has a lot of options, and for simplicity they are packed up // in a maco_options object. First, create the maco_options object with default values. maco_options opt("es"); // then, set required options on/off opt.QuantitiesDetection = false; //deactivate ratio/currency/magnitudes detection opt.AffixAnalysis = true; opt.MultiwordsDetection = true; opt.NumbersDetection = true; opt.PunctuationDetection = true; opt.DatesDetection = true; opt.QuantitiesDetection = false; opt.DictionarySearch = true; opt.ProbabilityAssignment = true; opt.NERecognition = NER_BASIC; // alternatively, you can set active modules in a single call: // opt.set_active_modules(true, true, true, true, true, false, true, true, NER_BASIC, false); // and provide files for morphological submodules. Note that it is not necessary // to set opt.QuantitiesFile, since Quantities module was deactivated. opt.LocutionsFile=path+"locucions.dat"; opt.AffixFile=path+"afixos.dat"; opt.ProbabilityFile=path+"probabilitats.dat"; opt.DictionaryFile=path+"maco.db"; opt.NPdataFile=path+"np.dat"; opt.PunctuationFile=path+"../common/punct.dat"; // alternatively, you can set the files in a single call: // opt.set_data_files(path+"locucions.dat", "", path+"afixos.dat", // path+"probabilitats.dat", path+"maco.db", // path+"np.dat", path+"../common/punct.dat", ""); // create the analyzer with the just build set of maco_options maco morfo(opt); // create a hmm tagger for spanish (with retokenization ability, and forced // to choose only one tag per word) hmm_tagger tagger("es", path+"tagger.dat", true, true); // create chunker chart_parser parser(path+"grammar-dep.dat"); // create dependency parser dep_txala dep(path+"dep/dependences.dat", parser.get_start_symbol()); // get plain text input lines while not EOF. while (getline(cin,text)) { // tokenize input line into a list of words lw=tk.tokenize(text); // accumulate list of words in splitter buffer, returning a list of sentences. // The resulting list of sentences may be empty if the splitter has still not // enough evidence to decide that a complete sentence has been found. The list // may contain more than one sentence (since a single input line may consist // of several complete sentences). ls=sp.split(lw, false); // perform and output morphosyntactic analysis and disambiguation morfo.analyze(ls); tagger.analyze(ls); // Do whatever our application does with the analyzed sentences ProcessResults(ls); // clear temporary lists; lw.clear(); ls.clear(); } // No more lines to read. Make sure the splitter doesn't retain anything ls=sp.split(lw, true); // analyze sentence(s) which might be lingering in the buffer, if any. morfo.analyze(ls); tagger.analyze(ls); // Process last sentence(s) ProcessResults(ls); }
The processing performed on the obtained results would obviously depend on the goal of the application (translation, indexation, etc.). In order to illustrate the structure of the linguistic data objects, a simple procedure is presented below, in which the processing consists of merely printing the results to stdout in XML format.
void ProcessResults(const list<sentence> &ls) { list<sentence>::const_iterator s; word::const_iterator a; //iterator over all analysis of a word sentence::const_iterator w; // for each sentence in list for (s=ls.begin(); s!=ls.end(); s++) { // print sentence XML tag cout<<"<SENT>"<<endl; // for each word in sentence for (w=s->begin(); w!=s->end(); w++) { // print word form, with PoS and lemma chosen by the tagger cout<<" <WORD form=\""<<w->get_form(); cout<<"\" lemma=\""<<w->get_lemma(); cout<<"\" pos=\""<<w->get_parole(); cout<<"\">"<<endl; // for each possible analysis in word, output lemma, parole and probability for (a=w->analysis_begin(); a!=w->analysis_end(); ++a) { // print analysis info cout<<" <ANALYSIS lemma=\""<<a->get_lemma(); cout<<"\" pos=\""<<a->get_parole(); cout<<"\" prob=\""<<a->get_prob(); cout<<"\"/>"<<endl; } // close word XML tag after list of analysis cout<<"</WORD>"<<endl; } // close sentence XML tag cout<<"</SENT>"<<endl; } }
The above sample program may be found in /src/main/simple_examples/sample.cc in FreeLing tarball.
Once you have compiled and installed FreeLing, you can build this
sample program (or any other you may want to write) with the command:
g++ -o sample sample.cc -lmorfo -ldb_cxx -lpcre -lomlet -fries -lboost_filesystem
Check the README file in the directory to learn more about compiling and using the sample programs.
Option -lmorfo links with libmorfo library, which is the final result of the FreeLing compilation process. The oher options refer to other libraries required by FreeLing.
You may have to add some -I and/or -L options to the compilation command depending on where the headers and code of required libraries are located. For instance, if you installed some of the libraries in /usr/local/mylib instead of the default place /usr/local, you'll have to add the options -I/usr/local/mylib/include -L/usr/local/mylib/lib to the command above.
Lluís Padró 2010-09-02