pyDelphin
Python libraries for DELPH-IN

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master
develop

NOTE for previous pyDelphin users: Recent versions of pyDelphin may have backwards-incompatible changes with prior versions. Please file an issue if you have trouble upgrading.

pyDelphin is a set of Python libraries for the processing of DELPH-IN data. It doesn't aim to do heavy tasks like parsing or treebanking, but rather to provide Python modules for loading a variety of DELPH-IN formats, such as [incr tsdb()] profiles or Minimal Recursion Semantics representations. These modules offer a programmatic interface to the data to enable developers or researchers to boostrap their own tools without having to re-invent the wheel. pyDelphin also provides a front-end tool for accomplishing some tasks such as refreshing [incr tsdb()] profiles to a new schema, creating sub-profiles, or converting between MRS representations (SimpleMRS, MRS XML, DMRS, etc.).

• Documentation
• Usage Examples
• Installation and Requirements
• Libraries

Documentation

API documentation is developing on the wiki. Help is appreciated!

Usage Examples

Here's a brief example of using the itsdb library:

>>> from delphin import itsdb
>>> prof = itsdb.ItsdbProfile('/home/goodmami/logon/dfki/jacy/tsdb/gold/mrs')
>>> for row in prof.read_table('item'):
...     print(row.get('i-input'))
雨 が 降っ た ．
太郎 が 吠え た ．
窓 が 開い た ．
太郎 が 次郎 を 追っ た ．
[...]
>>> next(prof.read_table('result')).get('derivation')
'(utterance-root (91 utterance_rule-decl-finite -0.723739 0 4 (90 head_subj_rule -1.05796 0 4 (87 hf-complement-rule -0.50201 0 2 (86 quantify-n-rule -0.32216 0 1 (5 ame-noun 0 0 1 ("雨" 1 "\\"雨\\""))) (6 ga 0.531537 1 2 ("が" 2 "\\"が\\""))) (89 vstem-vend-rule -0.471785 2 4 (88 t-lexeme-c-stem-infl-rule 0.120963 2 3 (14 furu_1 0 2 3 ("降っ" 3 "\\"降っ\\""))) (24 ta-end -0.380719 3 4 ("た" 4 "\\"た\\""))))))'

Here's an example of loading a SimpleMRS representation:

>>> from delphin.codecs import simplemrs
>>> m = simplemrs.loads_one('[ LTOP: h1 INDEX: e2 [ e TENSE: PAST MOOD: INDICATIVE PROG: - PERF: - SF: PROP ASPECT: DEFAULT_ASPECT PASS: - ] RELS: < [ udef_q_rel<0:1> LBL: h3 ARG0: x6 [ x PERS: 3 ] RSTR: h5 BODY: h4 ] [ "_ame_n_rel"<0:1> LBL: h7 ARG0: x6 ] [ "_furu_v_1_rel"<2:3> LBL: h8 ARG0: e2 ARG1: x6 ] > HCONS: < h5 qeq h7 > ]')
>>> m.ltop
'h1'
>>> for p in m.preds():
...     print('{}|{}|{}|{}'.format(p.string, p.lemma, p.pos, p.sense))
... 
udef_q_rel|udef|q|None
"_ame_n_rel"|ame|n|None
"_furu_v_1_rel"|furu|v|1
>>> print(simplemrs.dumps_one(m, pretty_print=True))
[ TOP: h1
  INDEX: e2 [ e TENSE: PAST MOOD: INDICATIVE PROG: - PERF: - SF: PROP ASPECT: DEFAULT_ASPECT PASS: - ]
  RELS: < [ udef_q_rel<0:1> LBL: h3 ARG0: x6 [ x PERS: 3 ] RSTR: h5 BODY: h4 ]
          [ "_ame_n_rel"<0:1> LBL: h7 ARG0: x6 ]
          [ "_furu_v_1_rel"<2:3> LBL: h8 ARG0: e2 ARG1: x6 ] >
  HCONS: < h5 qeq h7 > ]

Here is TDL introspection:

>>> from delphin import tdl
>>> f = open('/home/goodmami/logon/lingo/erg/fundamentals.tdl', 'r')
>>> types = {t.identifier: t for t in tdl.parse(f)}
>>> types['basic_word'].supertypes
['word_or_infl_rule', 'word_or_punct_rule']
>>> types['basic_word'].features()
[('SYNSEM', <TdlDefinition object at 140559634120136>), ('TOKENS', <TdlDefinition object at 140559631479864>), ('ORTH', <TdlDefinition object at 140559631479000>)]
>>> types['basic_word'].coreferences
[('#rb', ['ORTH.RB', 'TOKENS.+LAST.+TRAIT.+RB']), ('#to', ['SYNSEM.LKEYS.KEYREL.CTO', 'ORTH.TO', 'TOKENS.+LAST.+TO']), ('#lb', ['ORTH.LB', 'TOKENS.+LIST.FIRST.+TRAIT.+LB']), ('#form', ['ORTH.FORM', 'TOKENS.+LIST.FIRST.+FORM']), ('#tl', ['SYNSEM.PHON.ONSET.--TL', 'TOKENS.+LIST']), ('#from', ['SYNSEM.LKEYS.KEYREL.CFROM', 'ORTH.FROM', 'TOKENS.+LIST.FIRST.+FROM']), ('#class', ['ORTH.CLASS', 'TOKENS.+LIST.FIRST.+CLASS'])]

And here's how to compile, parse, and generate with the ACE wrapper:

>>> from delphin.interfaces import ace
>>> ace.compile('../jacy/ace/config.tdl', 'jacy.dat')
[...]
>>> ace.parse('jacy.dat', '犬 が 吠える')
{'SENT': '犬 が 吠える', 'NOTES': ['1 readings, added 183 / 54 edges to chart (22 fully instantiated, 26 actives used, 11 passives used)\tRAM: 730k'], 'WARNINGS': [], 'RESULTS': [{'DERIV': '(267 utterance_rule-decl-finite 4.367251 0 3 (266 head_subj_rule 2.906826 0 3 (263 hf-complement-rule -0.956762 0 2 (262 quantify-n-rule 0.215732 0 1 (10 inu-noun 0.049650 0 1 ("犬" 7 "token [ +FORM \\"犬\\" +FROM \\"0\\" +TO \\"1\\" +ID diff-list [ LIST list LAST list ] +POS pos [ +TAGS null +PRBS null ] +CLASS non_ne [ +INITIAL luk ] +TRAIT token_trait +PRED predsort +CARG \\"犬\\" ]"))) (17 ga 0.150269 1 2 ("が" 8 "token [ +FORM \\"が\\" +FROM \\"2\\" +TO \\"3\\" +ID diff-list [ LIST list LAST list ] +POS pos [ +TAGS null +PRBS null ] +CLASS non_ne [ +INITIAL luk ] +TRAIT token_trait +PRED predsort +CARG \\"が\\" ]"))) (265 unary-vstem-vend-rule 3.336552 2 3 (264 ru-lexeme-infl-rule 2.257695 2 3 (18 hoeru_1 0.000000 2 3 ("吠える" 9 "token [ +FORM \\"吠える\\" +FROM \\"4\\" +TO \\"7\\" +ID diff-list [ LIST list LAST list ] +POS pos [ +TAGS null +PRBS null ] +CLASS non_ne [ +INITIAL luk ] +TRAIT token_trait +PRED predsort +CARG \\"吠える\\" ]"))))))', 'MRS': '[ LTOP: h0 INDEX: e2 [ e TENSE: pres MOOD: indicative PROG: - PERF: - ASPECT: default_aspect PASS: - SF: prop ] RELS: < [ udef_q_rel<0:1> LBL: h4 ARG0: x3 [ x PERS: 3 ] RSTR: h5 BODY: h6 ]  [ "_inu_n_rel"<0:1> LBL: h7 ARG0: x3 ]  [ "_hoeru_v_1_rel"<4:7> LBL: h1 ARG0: e2 ARG1: x3 ] > HCONS: < h0 qeq h1 h5 qeq h7 > ]'}], 'ERRORS': []}
>>> res1 = ace.parse('jacy.dat', '犬 が 吠える')['RESULTS'][0]['MRS']
>>> ace.generate('jacy.dat', res1)
{'WARNING': None, 'ERROR': None, 'SENT': None, 'NOTE': None, 'RESULTS': ['犬 が 吠える']}

Installation and Requirements

pyDelphin is developed for Python 3 (3.3+), but it has also been tested to work with Python 2.7. Optional requirements include:

• NetworkX for MRS isomorphism checking
• Pygments for TDL and SimpleMRS syntax highlighting
• tikz-dependency, while not a Python requirement, is needed for compiling LaTeX documents using exported DMRSs

pyDelphin itself does not need to be installed to be used. You can adjust PYTHONPATH to include the pyDelphin directory.

If you would rather install it, however, it is available on PyPI:

$ pip install pydelphin

Sub-packages

The following packages/modules are available:

• derivation: Derivation trees
• itsdb: [incr tsdb()] profiles
• mrs: Minimal Recursion Semantics
• tdl: Type-Description Language
• tfs: Typed-Feature Structures
• extra.highlight: Pygments-based syntax highlighting (currently just for TDL and SimpleMRS)
• extra.latex: Formatting for LaTeX (just DMRS)
• interfaces.ace: Python wrapper for common tasks using ACE

Contributors

• Michael Wayne Goodman (primary author)
• T.J. Trimble (packaging, derivations, ACE)
• Guy Emerson (MRS)
• Alex Kuhnle (MRS)

Related Software

• https://github.com/wpm/Ruby-DELPH-IN
• https://github.com/ned2/typediff
• Also, on the DELPH-IN wiki:
  • http://moin.delph-in.net/
  • http://moin.delph-in.net/ToolsTop
  • http://moin.delph-in.net/DelphinApplications