Add util.filter_spans helper (#3686)

spacy/tests/doc/test_span.py

@@ -6,6 +6,7 @@ from spacy.attrs import ORTH, LENGTH
 from spacy.tokens import Doc, Span
 from spacy.vocab import Vocab
 from spacy.errors import ModelsWarning
+from spacy.util import filter_spans
 
 from ..util import get_doc
 
@@ -219,3 +220,21 @@ def test_span_ents_property(doc):
     assert sentences[2].ents[0].label_ == "PRODUCT"
     assert sentences[2].ents[0].start == 11
     assert sentences[2].ents[0].end == 14
+
+
+def test_filter_spans(doc):
+    # Test filtering duplicates
+    spans = [doc[1:4], doc[6:8], doc[1:4], doc[10:14]]
+    filtered = filter_spans(spans)
+    assert len(filtered) == 3
+    assert filtered[0].start == 1 and filtered[0].end == 4
+    assert filtered[1].start == 6 and filtered[1].end == 8
+    assert filtered[2].start == 10 and filtered[2].end == 14
+    # Test filtering overlaps with longest preference
+    spans = [doc[1:4], doc[1:3], doc[5:10], doc[7:9], doc[1:4]]
+    filtered = filter_spans(spans)
+    assert len(filtered) == 2
+    assert len(filtered[0]) == 3
+    assert len(filtered[1]) == 5
+    assert filtered[0].start == 1 and filtered[0].end == 4
+    assert filtered[1].start == 5 and filtered[1].end == 10

spacy/util.py

@@ -571,6 +571,28 @@ def itershuffle(iterable, bufsize=1000):
         raise StopIteration
 
 
+def filter_spans(spans):
+    """Filter a sequence of spans and remove duplicates or overlaps. Useful for
+    creating named entities (where one token can only be part of one entity) or
+    when merging spans with `Retokenizer.merge`. When spans overlap, the (first)
+    longest span is preferred over shorter spans.
+
+    spans (iterable): The spans to filter.
+    RETURNS (list): The filtered spans.
+    """
+    get_sort_key = lambda span: (span.end - span.start, span.start)
+    sorted_spans = sorted(spans, key=get_sort_key, reverse=True)
+    result = []
+    seen_tokens = set()
+    for span in sorted_spans:
+        # Check for end - 1 here because boundaries are inclusive
+        if span.start not in seen_tokens and span.end - 1 not in seen_tokens:
+            result.append(span)
+        seen_tokens.update(range(span.start, span.end))
+    result = sorted(result, key=lambda span: span.start)
+    return result
+
+
 def to_bytes(getters, exclude):
     serialized = OrderedDict()
     for key, getter in getters.items():

website/docs/api/top-level.md

@@ -654,6 +654,27 @@ for batching. Larger `buffsize` means less bias.
 | `buffsize` | int      | Items to hold back.    |
 | **YIELDS** | iterable | The shuffled iterator. |
 
+### util.filter_spans {#util.filter_spans tag="function" new="2.1.4"}
+
+Filter a sequence of [`Span`](/api/span) objects and remove duplicates or
+overlaps. Useful for creating named entities (where one token can only be part
+of one entity) or when merging spans with
+[`Retokenizer.merge`](/api/doc#retokenizer.merge). When spans overlap, the
+(first) longest span is preferred over shorter spans.
+
+> #### Example
+>
+> ```python
+> doc = nlp("This is a sentence.")
+> spans = [doc[0:2], doc[0:2], doc[0:4]]
+> filtered = filter_spans(spans)
+> ```
+
+| Name        | Type     | Description          |
+| ----------- | -------- | -------------------- |
+| `spans`     | iterable | The spans to filter. |
+| **RETURNS** | list     | The filtered spans.  |
+
 ## Compatibility functions {#compat source="spacy/compaty.py"}
 
 All Python code is written in an **intersection of Python 2 and Python 3**. This