U eg @sdZddlZddlZddlZddlZddlZddgddgddZd d gdd gd dZd gd ddgddZ dgddddddddgddZ dgddgddZ dgddgddZ dgdgddZ dgddgddZdgdgddZdgdgddZddd dd d!ddddg ZeeeZeee e e e e eeed" ZeZdd gZGd#d$d$Zgfd%d&ZdEd(d)Zd*d+Zd,d-Zd.d/Zd0d1Zd2d3ZdFd4d5Z d6d7Z!d8d9Z"dGd:d;Z#dd?Z%d@dAZ&dBdCZ'e(dDkre&e'dS)Ha Overview ======== Chat-80 was a natural language system which allowed the user to interrogate a Prolog knowledge base in the domain of world geography. It was developed in the early '80s by Warren and Pereira; see ``https://www.aclweb.org/anthology/J82-3002.pdf`` for a description and ``http://www.cis.upenn.edu/~pereira/oldies.html`` for the source files. This module contains functions to extract data from the Chat-80 relation files ('the world database'), and convert then into a format that can be incorporated in the FOL models of ``nltk.sem.evaluate``. The code assumes that the Prolog input files are available in the NLTK corpora directory. The Chat-80 World Database consists of the following files:: world0.pl rivers.pl cities.pl countries.pl contain.pl borders.pl This module uses a slightly modified version of ``world0.pl``, in which a set of Prolog rules have been omitted. The modified file is named ``world1.pl``. Currently, the file ``rivers.pl`` is not read in, since it uses a list rather than a string in the second field. Reading Chat-80 Files ===================== Chat-80 relations are like tables in a relational database. The relation acts as the name of the table; the first argument acts as the 'primary key'; and subsequent arguments are further fields in the table. In general, the name of the table provides a label for a unary predicate whose extension is all the primary keys. For example, relations in ``cities.pl`` are of the following form:: 'city(athens,greece,1368).' Here, ``'athens'`` is the key, and will be mapped to a member of the unary predicate *city*. The fields in the table are mapped to binary predicates. The first argument of the predicate is the primary key, while the second argument is the data in the relevant field. Thus, in the above example, the third field is mapped to the binary predicate *population_of*, whose extension is a set of pairs such as ``'(athens, 1368)'``. An exception to this general framework is required by the relations in the files ``borders.pl`` and ``contains.pl``. These contain facts of the following form:: 'borders(albania,greece).' 'contains0(africa,central_africa).' We do not want to form a unary concept out the element in the first field of these records, and we want the label of the binary relation just to be ``'border'``/``'contain'`` respectively. In order to drive the extraction process, we use 'relation metadata bundles' which are Python dictionaries such as the following:: city = {'label': 'city', 'closures': [], 'schema': ['city', 'country', 'population'], 'filename': 'cities.pl'} According to this, the file ``city['filename']`` contains a list of relational tuples (or more accurately, the corresponding strings in Prolog form) whose predicate symbol is ``city['label']`` and whose relational schema is ``city['schema']``. The notion of a ``closure`` is discussed in the next section. Concepts ======== In order to encapsulate the results of the extraction, a class of ``Concept`` objects is introduced. A ``Concept`` object has a number of attributes, in particular a ``prefLabel`` and ``extension``, which make it easier to inspect the output of the extraction. In addition, the ``extension`` can be further processed: in the case of the ``'border'`` relation, we check that the relation is symmetric, and in the case of the ``'contain'`` relation, we carry out the transitive closure. The closure properties associated with a concept is indicated in the relation metadata, as indicated earlier. The ``extension`` of a ``Concept`` object is then incorporated into a ``Valuation`` object. Persistence =========== The functions ``val_dump`` and ``val_load`` are provided to allow a valuation to be stored in a persistent database and re-loaded, rather than having to be re-computed each time. Individuals and Lexical Items ============================= As well as deriving relations from the Chat-80 data, we also create a set of individual constants, one for each entity in the domain. The individual constants are string-identical to the entities. For example, given a data item such as ``'zloty'``, we add to the valuation a pair ``('zloty', 'zloty')``. In order to parse English sentences that refer to these entities, we also create a lexical item such as the following for each individual constant:: PropN[num=sg, sem=<\P.(P zloty)>] -> 'Zloty' The set of rules is written to the file ``chat_pnames.cfg`` in the current directory. Nborders symmetricregionborderz borders.pl)rel_nameclosuresschemafilenameZ contains0 transitivecontainz contain.plcitycountry populationz cities.plZlatitudeZ longitudeZareaZcapitalcurrencyz countries.plZcircle_of_latitudedegreesz world1.plZcircle_of_longitude continentZ in_continentoceanseacontains circle_of_latcircle_of_long) rrr r rrrrrrc@sZeZdZdZggefddZddZddZdd Zd d Z d d Z ddZ ddZ dS)Conceptzc A Concept class, loosely based on SKOS (https://www.w3.org/TR/swbp-skos-core-guide/). cCs0||_||_||_||_||_tt||_dS)a :param prefLabel: the preferred label for the concept :type prefLabel: str :param arity: the arity of the concept :type arity: int :param altLabels: other (related) labels :type altLabels: list :param closures: closure properties of the extension (list items can be ``symmetric``, ``reflexive``, ``transitive``) :type closures: list :param extension: the extensional value of the concept :type extension: set N) prefLabelarity altLabelsr _extensionsortedlist extension)selfrrrrrr P/var/www/html/assets/scripts/venv/lib/python3.8/site-packages/nltk/sem/chat80.py__init__s zConcept.__init__cCsd|j|j|jS)Nz&Label = '{}' Arity = {} Extension = {})formatrrrrr r r!__str__s zConcept.__str__cCs d|jS)Nz Concept('%s'))rr$r r r!__repr__!szConcept.__repr__cCs"|j|tt|j|_|jS)z Add more data to the ``Concept``'s extension set. :param data: a new semantic value :type data: string or pair of strings :rtype: set )raddrrr)rdatar r r!augment$s zConcept.augmentcCs8i}|D]*\}}||kr(|||q|g||<q|S)z[ Convert a set of pairs into an adjacency linked list encoding of a graph. append)rsgxyr r r! _make_graph1s   zConcept._make_graphcCsL|D]B}||D]4}||kr||D]}|||kr$|||q$qq|S)zY Compute the transitive closure of a graph represented as a linked list. r*)rr-r.adjacentr/r r r! _transclose=s   zConcept._transclosecCs2g}|D] }||D]}|||fqqt|S)zL Convert an adjacency linked list back into a set of pairs. )r+set)rr-pairsnoder1r r r! _make_pairsJs  zConcept._make_pairsc Csddlm}||jstd|jkr\g}|jD]\}}|||fq.t|}|j||_d|jkr||j}| |}| |}|j||_t t |j|_ dS)z Close a binary relation in the ``Concept``'s extension set. :return: a new extension for the ``Concept`` in which the relation is closed under a given property r)is_relrr N)nltk.semr7rAssertionErrorrr+r3unionr0r2r6rrr) rr7r4r.r/symallclosedZtransr r r!closeTs      z Concept.closeN) __name__ __module__ __qualname____doc__r3r"r%r&r)r0r2r6r>r r r r!rs    rc Csng}d}|d}|dd}t||}|tkr@|t||||D]$} || } |t| ||| |qD|S)a Convert a file of Prolog clauses into a list of ``Concept`` objects. :param filename: filename containing the relations :type filename: str :param rel_name: name of the relation :type rel_name: str :param schema: the schema used in a set of relational tuples :type schema: list :param closures: closure properties for the extension of the concept :type closures: list :return: a list of ``Concept`` objects :rtype: list rN) _str2records not_unaryr+ unary_conceptindexbinary_concept) r rrrconceptssubjpkeyfieldsrecordsfieldobjr r r!clause2conceptsls   rPFc Csddl}t||}||}|}|r2|dd} |D]&} |d| | |r:td| | q:||rztd||dS)a Convert a file of Prolog clauses into a database table. This is not generic, since it doesn't allow arbitrary schemas to be set as a parameter. Intended usage:: cities2table('cities.pl', 'city', 'city.db', verbose=True, setup=True) :param filename: filename containing the relations :type filename: str :param rel_name: name of the relation :type rel_name: str :param dbname: filename of persistent store :type schema: str rNzICREATE TABLE city_table (City text, Country text, Population int)Z city_tablezinsert into %s values (?,?,?)zinserting values into %s: zCommitting update to %s)sqlite3rDconnectcursorexecuteprintcommitr>) r rdbnameverbosesetuprQrM connectioncurZ table_nametr r r! cities2tables"   r]c Csnddl}z.tj|}|t|}|}||WSt|j fk rhddl }| d|YnXdS)z Execute an SQL query over a database. :param dbname: filename of persistent store :type schema: str :param query: SQL query :type rel_name: str rNz=Make sure the database file %s is installed and uncompressed.) rQnltkr(findrRstrrSrT ValueErrorZOperationalErrorwarningswarn)rWqueryrQpathrZr[rbr r r! sql_querys  rfcCshg}tjjd|dd}|D]B}||r t|dd|}tdd|}|d}||q |S)zO Read a file into memory and convert each relation clause into a list. zcorpora/chat80/%stext)r#z\(z\)\.$,) r^r(load splitlines startswithresubsplitr+)r relZrecscontentslinerecordr r r!rDs    rDcCs,t|dtd}|D]}|||q|S)a Make a unary concept out of the primary key in a record. A record is a list of entities in some relation, such as ``['france', 'paris']``, where ``'france'`` is acting as the primary key. :param label: the preferred label for the concept :type label: string :param subj: position in the record of the subject of the predicate :type subj: int :param records: a list of records :type records: list of lists :return: ``Concept`` of arity 1 :rtype: Concept rC)rr)rr3r))labelrJrMcrsr r r!rFsrFcCsV|dks|dks|d}t|d|td}|D]}|||||fq.||S)a$ Make a binary concept out of the primary key and another field in a record. A record is a list of entities in some relation, such as ``['france', 'paris']``, where ``'france'`` is acting as the primary key, and ``'paris'`` stands in the ``'capital_of'`` relation to ``'france'``. More generally, given a record such as ``['a', 'b', 'c']``, where label is bound to ``'B'``, and ``obj`` bound to 1, the derived binary concept will have label ``'B_of'``, and its extension will be a set of pairs such as ``('a', 'b')``. :param label: the base part of the preferred label for the concept :type label: str :param closures: closure properties for the extension of the concept :type closures: list :param subj: position in the record of the subject of the predicate :type subj: int :param obj: position in the record of the object of the predicate :type obj: int :param records: a list of records :type records: list of lists :return: ``Concept`` of arity 2 :rtype: Concept rr Z_of)rrr)rr3r)r>)rtrrJrOrMrursr r r!rHsrHc Csi}|D]z}|d}|d}|d}|d}t||||}|D]B}|j} | |krx|jD]} || | qV|| q>||| <q>q|S)aI Given a list of relation metadata bundles, make a corresponding dictionary of concepts, indexed by the relation name. :param rels: bundle of metadata needed for constructing a concept :type rels: list(dict) :return: a dictionary of concepts, indexed by the relation name. :rtype: dict(str): Concept rrrr )rPrrr)r>) relsrIrprrrr Z concept_listrurtr(r r r!process_bundle s   rxcCsbg}|D]}||j|jfq|r(d}|rZddlm}|i}||t||d}|S|SdS)aN Convert a list of ``Concept`` objects into a list of (label, extension) pairs; optionally create a ``Valuation`` object. :param concepts: concepts :type concepts: list(Concept) :param read: if ``True``, ``(symbol, set)`` pairs are read into a ``Valuation`` :type read: bool :rtype: list or Valuation Tr ValuationlexiconN)r+rrr8rzupdate label_indivs)rIreadr|valsrurzvalr r r!make_valuation=s    rcCs:t|}t|dd}t|d}|||dS)aX Make a ``Valuation`` from a list of relation metadata bundles and dump to persistent database. :param rels: bundle of metadata needed for constructing a concept :type rels: list of dict :param db: name of file to which data is written. The suffix '.db' will be automatically appended. :type db: str TrnN)rxvaluesrshelveopenr}r>)rwdbrI valuationZdb_outr r r!val_dumpZs    rcCsL|d}t|tjs&td|n"t|}ddlm}||}|SdS)z Load a ``Valuation`` from a persistent database. :param db: name of file from which data is read. The suffix '.db' should be omitted from the name. :type db: str .dbCannot read file: %srryN) osaccessR_OKsysexitrrr8rz)rrWZdb_inrzrr r r!val_loadns  rc CsN|j}dd|D}|r@t|}tdd}||W5QRX|||S)z Assign individual constants to the individuals in the domain of a ``Valuation``. Given a valuation with an entry of the form ``{'rel': {'a': True}}``, add a new entry ``{'a': 'a'}``. :type valuation: Valuation :rtype: Valuation cSsg|] }||fqSr r ).0er r r! sz label_indivs..zchat_pnames.cfgw)domainmake_lexr writelinesr})rr|rr4lexoutfiler r r!r~s   r~c Cs\g}d}||d}|D]<}|d}dd|D}d|}|||f}||q|S)aO Create lexical CFG rules for each individual symbol. Given a valuation with an entry of the form ``{'zloty': 'zloty'}``, create a lexical rule for the proper name 'Zloty'. :param symbols: a list of individual constants in the semantic representation :type symbols: sequence -- set(str) :rtype: list(str) z ################################################################## # Lexical rules automatically generated by running 'chat80.py -x'. ################################################################## z(PropN[num=sg, sem=<\P.(P %s)>] -> '%s'\n_cSsg|] }|qSr ) capitalize)rpr r r!rszmake_lex..)r+rojoin) symbolsrheadertemplater,partsZcapsZpnameruler r r!rs      rcCs.t|tr|f}dd|D}t|}|S)a Build a list of concepts corresponding to the relation names in ``items``. :param items: names of the Chat-80 relations to extract :type items: list(str) :return: the ``Concept`` objects which are extracted from the relations :rtype: list(Concept) cSsg|] }t|qSr ) item_metadata)rrr r r!rszconcepts..) isinstancer`rxr)itemsrw concept_mapr r r!rIs rIcCs0ddl}ddlm}d}||d}|jdddd|jdd d d d d |jddddd d |jddddd|jdddddd |jddddd d!|jd"d#dd$d%d!|jd&d'dd(d)d!|\}}|jr|jr|d*|jr|j r|jd+}t d,|t t |j| dn|jdk r`|jd+}t|tjsT| d-|n t|j}ntt } | } |jrtd.d/| D} | D]\} } t | | q| d|jr| D]}t |t q|jrt | |j| dn:|jr|j r t d0t| dd1nt| dd2}t |dS)3Nr) OptionParserz Extract data from the Chat-80 Prolog files and convert them into a Valuation object for use in the NLTK semantics package. ) descriptionTF)rXrvocabz-sz--storeoutdbzstore a valuation in DBZDB)desthelpmetavarz-lz--loadindbzload a stored valuation from DBz-cz --concepts store_truez%print concepts instead of a valuation)actionrz-rz --relationrtzEprint concept with label REL (check possible labels with '-v' option)ZRELz-qz--quiet store_falserXzdon't print out progress info)rrrz-xz--lexrz6szmain..zWriting out lexical rulesr{r)roptparser set_defaults add_option parse_argsrrerrorrXrUrrwrrrrrrxrrrrIrtrr)rrroptsoptionsargsrrWrrrIrrrtrur r r!mains                rcCs*ttdtddD] }t|qdS)z: Print out every row from the 'city.db' database. z-Using SQL to extract rows from 'city.db' RDB.zcorpora/city_database/city.dbzSELECT * FROM city_tableN)rUrf)rowr r r!sql_demoMsr__main__)FF)FF)F))rBrrmrrZ nltk.datar^rrr r rrrrrrrtuplerrrrwrErrPr]rfrDrFrHrxrrrr~rrIrrr?r r r r! su   v ( (& & # i