spaCy/spacy/pipeline/_parser_internals/nonproj.pyx

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# cython: profile=True, infer_types=True
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"""Implements the projectivize/deprojectivize mechanism in Nivre & Nilsson 2005
for doing pseudo-projective parsing implementation uses the HEAD decoration
scheme.
"""
from copy import copy
from ...tokens.doc cimport Doc, set_children_from_heads
from ...errors import Errors
DELIMITER = '||'
def ancestors(tokenid, heads):
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# Returns all words going from the word up the path to the root. The path
# to root cannot be longer than the number of words in the sentence. This
# function ends after at most len(heads) steps, because it would otherwise
# loop indefinitely on cycles.
head = tokenid
cnt = 0
while heads[head] != head and cnt < len(heads):
head = heads[head]
cnt += 1
yield head
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if head is None:
break
def contains_cycle(heads):
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# in an acyclic tree, the path from each word following the head relation
# upwards always ends at the root node
for tokenid in range(len(heads)):
seen = set([tokenid])
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for ancestor in ancestors(tokenid, heads):
if ancestor in seen:
return seen
seen.add(ancestor)
return None
def is_nonproj_arc(tokenid, heads):
# definition (e.g. Havelka 2007): an arc h -> d, h < d is non-projective
# if there is a token k, h < k < d such that h is not
# an ancestor of k. Same for h -> d, h > d
head = heads[tokenid]
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if head == tokenid: # root arcs cannot be non-projective
return False
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elif head is None: # unattached tokens cannot be non-projective
return False
Improve spacy.gold (no GoldParse, no json format!) (#5555) * Update errors * Remove beam for now (maybe) Remove beam_utils Update setup.py Remove beam * Remove GoldParse WIP on removing goldparse Get ArcEager compiling after GoldParse excise Update setup.py Get spacy.syntax compiling after removing GoldParse Rename NewExample -> Example and clean up Clean html files Start updating tests Update Morphologizer * fix error numbers * fix merge conflict * informative error when calling to_array with wrong field * fix error catching * fixing language and scoring tests * start testing get_aligned * additional tests for new get_aligned function * Draft create_gold_state for arc_eager oracle * Fix import * Fix import * Remove TokenAnnotation code from nonproj * fixing NER one-to-many alignment * Fix many-to-one IOB codes * fix test for misaligned * attempt to fix cases with weird spaces * fix spaces * test_gold_biluo_different_tokenization works * allow None as BILUO annotation * fixed some tests + WIP roundtrip unit test * add spaces to json output format * minibatch utiltiy can deal with strings, docs or examples * fix augment (needs further testing) * various fixes in scripts - needs to be further tested * fix test_cli * cleanup * correct silly typo * add support for MORPH in to/from_array, fix morphologizer overfitting test * fix tagger * fix entity linker * ensure test keeps working with non-linked entities * pipe() takes docs, not examples * small bug fix * textcat bugfix * throw informative error when running the components with the wrong type of objects * fix parser tests to work with example (most still failing) * fix BiluoPushDown parsing entities * small fixes * bugfix tok2vec * fix renames and simple_ner labels * various small fixes * prevent writing dummy values like deps because that could interfer with sent_start values * fix the fix * implement split_sent with aligned SENT_START attribute * test for split sentences with various alignment issues, works * Return ArcEagerGoldParse from ArcEager * Update parser and NER gold stuff * Draft new GoldCorpus class * add links to to_dict * clean up * fix test checking for variants * Fix oracles * Start updating converters * Move converters under spacy.gold * Move things around * Fix naming * Fix name * Update converter to produce DocBin * Update converters * Allow DocBin to take list of Doc objects. * Make spacy convert output docbin * Fix import * Fix docbin * Fix compile in ArcEager * Fix import * Serialize all attrs by default * Update converter * Remove jsonl converter * Add json2docs converter * Draft Corpus class for DocBin * Work on train script * Update Corpus * Update DocBin * Allocate Doc before starting to add words * Make doc.from_array several times faster * Update train.py * Fix Corpus * Fix parser model * Start debugging arc_eager oracle * Update header * Fix parser declaration * Xfail some tests * Skip tests that cause crashes * Skip test causing segfault * Remove GoldCorpus * Update imports * Update after removing GoldCorpus * Fix module name of corpus * Fix mimport * Work on parser oracle * Update arc_eager oracle * Restore ArcEager.get_cost function * Update transition system * Update test_arc_eager_oracle * Remove beam test * Update test * Unskip * Unskip tests * add links to to_dict * clean up * fix test checking for variants * Allow DocBin to take list of Doc objects. * Fix compile in ArcEager * Serialize all attrs by default Move converters under spacy.gold Move things around Fix naming Fix name Update converter to produce DocBin Update converters Make spacy convert output docbin Fix import Fix docbin Fix import Update converter Remove jsonl converter Add json2docs converter * Allocate Doc before starting to add words * Make doc.from_array several times faster * Start updating converters * Work on train script * Draft Corpus class for DocBin Update Corpus Fix Corpus * Update DocBin Add missing strings when serializing * Update train.py * Fix parser model * Start debugging arc_eager oracle * Update header * Fix parser declaration * Xfail some tests Skip tests that cause crashes Skip test causing segfault * Remove GoldCorpus Update imports Update after removing GoldCorpus Fix module name of corpus Fix mimport * Work on parser oracle Update arc_eager oracle Restore ArcEager.get_cost function Update transition system * Update tests Remove beam test Update test Unskip Unskip tests * Add get_aligned_parse method in Example Fix Example.get_aligned_parse * Add kwargs to Corpus.dev_dataset to match train_dataset * Update nonproj * Use get_aligned_parse in ArcEager * Add another arc-eager oracle test * Remove Example.doc property Remove Example.doc Remove Example.doc Remove Example.doc Remove Example.doc * Update ArcEager oracle Fix Break oracle * Debugging * Fix Corpus * Fix eg.doc * Format * small fixes * limit arg for Corpus * fix test_roundtrip_docs_to_docbin * fix test_make_orth_variants * fix add_label test * Update tests * avoid writing temp dir in json2docs, fixing 4402 test * Update test * Add missing costs to NER oracle * Update test * Work on Example.get_aligned_ner method * Clean up debugging * Xfail tests * Remove prints * Remove print * Xfail some tests * Replace unseen labels for parser * Update test * Update test * Xfail test * Fix Corpus * fix imports * fix docs_to_json * various small fixes * cleanup * Support gold_preproc in Corpus * Support gold_preproc * Pass gold_preproc setting into corpus * Remove debugging * Fix gold_preproc * Fix json2docs converter * Fix convert command * Fix flake8 * Fix import * fix output_dir (converted to Path by typer) * fix var * bugfix: update states after creating golds to avoid out of bounds indexing * Improve efficiency of ArEager oracle * pull merge_sent into iob2docs to avoid Doc creation for each line * fix asserts * bugfix excl Span.end in iob2docs * Support max_length in Corpus * Fix arc_eager oracle * Filter out uannotated sentences in NER * Remove debugging in parser * Simplify NER alignment * Fix conversion of NER data * Fix NER init_gold_batch * Tweak efficiency of precomputable affine * Update onto-json default * Update gold test for NER * Fix parser test * Update test * Add NER data test * Fix convert for single file * Fix test * Hack scorer to avoid evaluating non-nered data * Fix handling of NER data in Example * Output unlabelled spans from O biluo tags in iob_utils * Fix unset variable * Return kept examples from init_gold_batch * Return examples from init_gold_batch * Dont return Example from init_gold_batch * Set spaces on gold doc after conversion * Add test * Fix spaces reading * Improve NER alignment * Improve handling of missing values in NER * Restore the 'cutting' in parser training * Add assertion * Print epochs * Restore random cuts in parser/ner training * Implement Doc.copy * Implement Example.copy * Copy examples at the start of Language.update * Don't unset example docs * Tweak parser model slightly * attempt to fix _guess_spaces * _add_entities_to_doc first, so that links don't get overwritten * fixing get_aligned_ner for one-to-many * fix indexing into x_text * small fix biluo_tags_from_offsets * Add onto-ner config * Simplify NER alignment * Fix NER scoring for partially annotated documents * fix indexing into x_text * fix test_cli failing tests by ignoring spans in doc.ents with empty label * Fix limit * Improve NER alignment * Fix count_train * Remove print statement * fix tests, we're not having nothing but None * fix clumsy fingers * Fix tests * Fix doc.ents * Remove empty docs in Corpus and improve limit * Update config Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com>
2020-06-26 20:34:12 +03:00
cdef int start, end
if head < tokenid:
start, end = (head+1, tokenid)
else:
start, end = (tokenid+1, head)
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for k in range(start, end):
for ancestor in ancestors(k, heads):
if ancestor is None: # for unattached tokens/subtrees
break
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elif ancestor == head: # normal case: k dominated by h
break
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else: # head not in ancestors: d -> h is non-projective
return True
return False
def is_nonproj_tree(heads):
# a tree is non-projective if at least one arc is non-projective
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return any(is_nonproj_arc(word, heads) for word in range(len(heads)))
def decompose(label):
return label.partition(DELIMITER)[::2]
def is_decorated(label):
return DELIMITER in label
def count_decorated_labels(gold_data):
freqs = {}
for example in gold_data:
Improve spacy.gold (no GoldParse, no json format!) (#5555) * Update errors * Remove beam for now (maybe) Remove beam_utils Update setup.py Remove beam * Remove GoldParse WIP on removing goldparse Get ArcEager compiling after GoldParse excise Update setup.py Get spacy.syntax compiling after removing GoldParse Rename NewExample -> Example and clean up Clean html files Start updating tests Update Morphologizer * fix error numbers * fix merge conflict * informative error when calling to_array with wrong field * fix error catching * fixing language and scoring tests * start testing get_aligned * additional tests for new get_aligned function * Draft create_gold_state for arc_eager oracle * Fix import * Fix import * Remove TokenAnnotation code from nonproj * fixing NER one-to-many alignment * Fix many-to-one IOB codes * fix test for misaligned * attempt to fix cases with weird spaces * fix spaces * test_gold_biluo_different_tokenization works * allow None as BILUO annotation * fixed some tests + WIP roundtrip unit test * add spaces to json output format * minibatch utiltiy can deal with strings, docs or examples * fix augment (needs further testing) * various fixes in scripts - needs to be further tested * fix test_cli * cleanup * correct silly typo * add support for MORPH in to/from_array, fix morphologizer overfitting test * fix tagger * fix entity linker * ensure test keeps working with non-linked entities * pipe() takes docs, not examples * small bug fix * textcat bugfix * throw informative error when running the components with the wrong type of objects * fix parser tests to work with example (most still failing) * fix BiluoPushDown parsing entities * small fixes * bugfix tok2vec * fix renames and simple_ner labels * various small fixes * prevent writing dummy values like deps because that could interfer with sent_start values * fix the fix * implement split_sent with aligned SENT_START attribute * test for split sentences with various alignment issues, works * Return ArcEagerGoldParse from ArcEager * Update parser and NER gold stuff * Draft new GoldCorpus class * add links to to_dict * clean up * fix test checking for variants * Fix oracles * Start updating converters * Move converters under spacy.gold * Move things around * Fix naming * Fix name * Update converter to produce DocBin * Update converters * Allow DocBin to take list of Doc objects. * Make spacy convert output docbin * Fix import * Fix docbin * Fix compile in ArcEager * Fix import * Serialize all attrs by default * Update converter * Remove jsonl converter * Add json2docs converter * Draft Corpus class for DocBin * Work on train script * Update Corpus * Update DocBin * Allocate Doc before starting to add words * Make doc.from_array several times faster * Update train.py * Fix Corpus * Fix parser model * Start debugging arc_eager oracle * Update header * Fix parser declaration * Xfail some tests * Skip tests that cause crashes * Skip test causing segfault * Remove GoldCorpus * Update imports * Update after removing GoldCorpus * Fix module name of corpus * Fix mimport * Work on parser oracle * Update arc_eager oracle * Restore ArcEager.get_cost function * Update transition system * Update test_arc_eager_oracle * Remove beam test * Update test * Unskip * Unskip tests * add links to to_dict * clean up * fix test checking for variants * Allow DocBin to take list of Doc objects. * Fix compile in ArcEager * Serialize all attrs by default Move converters under spacy.gold Move things around Fix naming Fix name Update converter to produce DocBin Update converters Make spacy convert output docbin Fix import Fix docbin Fix import Update converter Remove jsonl converter Add json2docs converter * Allocate Doc before starting to add words * Make doc.from_array several times faster * Start updating converters * Work on train script * Draft Corpus class for DocBin Update Corpus Fix Corpus * Update DocBin Add missing strings when serializing * Update train.py * Fix parser model * Start debugging arc_eager oracle * Update header * Fix parser declaration * Xfail some tests Skip tests that cause crashes Skip test causing segfault * Remove GoldCorpus Update imports Update after removing GoldCorpus Fix module name of corpus Fix mimport * Work on parser oracle Update arc_eager oracle Restore ArcEager.get_cost function Update transition system * Update tests Remove beam test Update test Unskip Unskip tests * Add get_aligned_parse method in Example Fix Example.get_aligned_parse * Add kwargs to Corpus.dev_dataset to match train_dataset * Update nonproj * Use get_aligned_parse in ArcEager * Add another arc-eager oracle test * Remove Example.doc property Remove Example.doc Remove Example.doc Remove Example.doc Remove Example.doc * Update ArcEager oracle Fix Break oracle * Debugging * Fix Corpus * Fix eg.doc * Format * small fixes * limit arg for Corpus * fix test_roundtrip_docs_to_docbin * fix test_make_orth_variants * fix add_label test * Update tests * avoid writing temp dir in json2docs, fixing 4402 test * Update test * Add missing costs to NER oracle * Update test * Work on Example.get_aligned_ner method * Clean up debugging * Xfail tests * Remove prints * Remove print * Xfail some tests * Replace unseen labels for parser * Update test * Update test * Xfail test * Fix Corpus * fix imports * fix docs_to_json * various small fixes * cleanup * Support gold_preproc in Corpus * Support gold_preproc * Pass gold_preproc setting into corpus * Remove debugging * Fix gold_preproc * Fix json2docs converter * Fix convert command * Fix flake8 * Fix import * fix output_dir (converted to Path by typer) * fix var * bugfix: update states after creating golds to avoid out of bounds indexing * Improve efficiency of ArEager oracle * pull merge_sent into iob2docs to avoid Doc creation for each line * fix asserts * bugfix excl Span.end in iob2docs * Support max_length in Corpus * Fix arc_eager oracle * Filter out uannotated sentences in NER * Remove debugging in parser * Simplify NER alignment * Fix conversion of NER data * Fix NER init_gold_batch * Tweak efficiency of precomputable affine * Update onto-json default * Update gold test for NER * Fix parser test * Update test * Add NER data test * Fix convert for single file * Fix test * Hack scorer to avoid evaluating non-nered data * Fix handling of NER data in Example * Output unlabelled spans from O biluo tags in iob_utils * Fix unset variable * Return kept examples from init_gold_batch * Return examples from init_gold_batch * Dont return Example from init_gold_batch * Set spaces on gold doc after conversion * Add test * Fix spaces reading * Improve NER alignment * Improve handling of missing values in NER * Restore the 'cutting' in parser training * Add assertion * Print epochs * Restore random cuts in parser/ner training * Implement Doc.copy * Implement Example.copy * Copy examples at the start of Language.update * Don't unset example docs * Tweak parser model slightly * attempt to fix _guess_spaces * _add_entities_to_doc first, so that links don't get overwritten * fixing get_aligned_ner for one-to-many * fix indexing into x_text * small fix biluo_tags_from_offsets * Add onto-ner config * Simplify NER alignment * Fix NER scoring for partially annotated documents * fix indexing into x_text * fix test_cli failing tests by ignoring spans in doc.ents with empty label * Fix limit * Improve NER alignment * Fix count_train * Remove print statement * fix tests, we're not having nothing but None * fix clumsy fingers * Fix tests * Fix doc.ents * Remove empty docs in Corpus and improve limit * Update config Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com>
2020-06-26 20:34:12 +03:00
proj_heads, deco_deps = projectivize(example.get_aligned("HEAD"),
example.get_aligned("DEP"))
Restructure Example with merged sents as default (#4632) * Switch to train_dataset() function in train CLI * Fixes for pipe() methods in pipeline components * Don't clobber `examples` variable with `as_example` in pipe() methods * Remove unnecessary traversals of `examples` * Update Parser.pipe() for Examples * Add `as_examples` kwarg to `pipe()` with implementation to return `Example`s * Accept `Doc` or `Example` in `pipe()` with `_get_doc()` (copied from `Pipe`) * Fixes to Example implementation in spacy.gold * Move `make_projective` from an attribute of Example to an argument of `Example.get_gold_parses()` * Head of 0 are not treated as unset * Unset heads are set to self rather than `None` (which causes problems while projectivizing) * Check for `Doc` (not just not `None`) when creating GoldParses for pre-merged example * Don't clobber `examples` variable in `iter_gold_docs()` * Add/modify gold tests for handling projectivity * In JSON roundtrip compare results from `dev_dataset` rather than `train_dataset` to avoid projectivization (and other potential modifications) * Add test for projective train vs. nonprojective dev versions of the same `Doc` * Handle ignore_misaligned as arg rather than attr Move `ignore_misaligned` from an attribute of `Example` to an argument to `Example.get_gold_parses()`, which makes it parallel to `make_projective`. Add test with old and new align that checks whether `ignore_misaligned` errors are raised as expected (only for new align). * Remove unused attrs from gold.pxd Remove `ignore_misaligned` and `make_projective` from `gold.pxd` * Restructure Example with merged sents as default An `Example` now includes a single `TokenAnnotation` that includes all the information from one `Doc` (=JSON `paragraph`). If required, the individual sentences can be returned as a list of examples with `Example.split_sents()` with no raw text available. * Input/output a single `Example.token_annotation` * Add `sent_starts` to `TokenAnnotation` to handle sentence boundaries * Replace `Example.merge_sents()` with `Example.split_sents()` * Modify components to use a single `Example.token_annotation` * Pipeline components * conllu2json converter * Rework/rename `add_token_annotation()` and `add_doc_annotation()` to `set_token_annotation()` and `set_doc_annotation()`, functions that set rather then appending/extending. * Rename `morphology` to `morphs` in `TokenAnnotation` and `GoldParse` * Add getters to `TokenAnnotation` to supply default values when a given attribute is not available * `Example.get_gold_parses()` in `spacy.gold._make_golds()` is only applied on single examples, so the `GoldParse` is returned saved in the provided `Example` rather than creating a new `Example` with no other internal annotation * Update tests for API changes and `merge_sents()` vs. `split_sents()` * Refer to Example.goldparse in iter_gold_docs() Use `Example.goldparse` in `iter_gold_docs()` instead of `Example.gold` because a `None` `GoldParse` is generated with ignore_misaligned and generating it on-the-fly can raise an unwanted AlignmentError * Fix make_orth_variants() Fix bug in make_orth_variants() related to conversion from multiple to one TokenAnnotation per Example. * Add basic test for make_orth_variants() * Replace try/except with conditionals * Replace default morph value with set
2019-11-25 18:03:28 +03:00
# set the label to ROOT for each root dependent
deco_deps = ['ROOT' if head == i else deco_deps[i]
for i, head in enumerate(proj_heads)]
# count label frequencies
for label in deco_deps:
if is_decorated(label):
freqs[label] = freqs.get(label, 0) + 1
return freqs
def projectivize(heads, labels):
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# Use the algorithm by Nivre & Nilsson 2005. Assumes heads to be a proper
# tree, i.e. connected and cycle-free. Returns a new pair (heads, labels)
# which encode a projective and decorated tree.
proj_heads = copy(heads)
smallest_np_arc = _get_smallest_nonproj_arc(proj_heads)
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if smallest_np_arc is None: # this sentence is already projective
return proj_heads, copy(labels)
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while smallest_np_arc is not None:
_lift(smallest_np_arc, proj_heads)
smallest_np_arc = _get_smallest_nonproj_arc(proj_heads)
deco_labels = _decorate(heads, proj_heads, labels)
return proj_heads, deco_labels
cpdef deprojectivize(Doc doc):
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# Reattach arcs with decorated labels (following HEAD scheme). For each
# decorated arc X||Y, search top-down, left-to-right, breadth-first until
# hitting a Y then make this the new head.
for i in range(doc.length):
label = doc.vocab.strings[doc.c[i].dep]
if DELIMITER in label:
new_label, head_label = label.split(DELIMITER)
new_head = _find_new_head(doc[i], head_label)
doc.c[i].head = new_head.i - i
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doc.c[i].dep = doc.vocab.strings.add(new_label)
set_children_from_heads(doc.c, 0, doc.length)
return doc
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def _decorate(heads, proj_heads, labels):
# uses decoration scheme HEAD from Nivre & Nilsson 2005
if (len(heads) != len(proj_heads)) or (len(proj_heads) != len(labels)):
raise ValueError(Errors.E082.format(n_heads=len(heads),
n_proj_heads=len(proj_heads),
n_labels=len(labels)))
deco_labels = []
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for tokenid, head in enumerate(heads):
if head != proj_heads[tokenid]:
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deco_labels.append(f"{labels[tokenid]}{DELIMITER}{labels[head]}")
else:
deco_labels.append(labels[tokenid])
return deco_labels
def _get_smallest_nonproj_arc(heads):
# return the smallest non-proj arc or None
# where size is defined as the distance between dep and head
# and ties are broken left to right
smallest_size = float('inf')
smallest_np_arc = None
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for tokenid, head in enumerate(heads):
size = abs(tokenid-head)
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if size < smallest_size and is_nonproj_arc(tokenid, heads):
smallest_size = size
smallest_np_arc = tokenid
return smallest_np_arc
def _lift(tokenid, heads):
# reattaches a word to it's grandfather
head = heads[tokenid]
ghead = heads[head]
# attach to ghead if head isn't attached to root else attach to root
heads[tokenid] = ghead if head != ghead else tokenid
def _find_new_head(token, headlabel):
# search through the tree starting from the head of the given token
# returns the id of the first descendant with the given label
# if there is none, return the current head (no change)
queue = [token.head]
while queue:
next_queue = []
for qtoken in queue:
for child in qtoken.children:
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if child.is_space:
continue
if child == token:
continue
if child.dep_ == headlabel:
return child
next_queue.append(child)
queue = next_queue
return token.head