from typing import Union, Iterator, Tuple

from ...symbols import NOUN, PROPN, PRON
from ...errors import Errors
from ...tokens import Doc, Span


def noun_chunks(doclike: Union[Doc, Span]) -> Iterator[Tuple[int, int, int]]:
    """Detect base noun phrases from a dependency parse. Works on Doc and Span."""
    # this iterator extracts spans headed by NOUNs starting from the left-most
    # syntactic dependent until the NOUN itself for close apposition and
    # measurement construction, the span is sometimes extended to the right of
    # the NOUN. Example: "eine Tasse Tee" (a cup (of) tea) returns "eine Tasse Tee"
    # and not just "eine Tasse", same for "das Thema Familie".
    # fmt: off
    labels = ["sb", "oa", "da", "nk", "mo", "ag", "ROOT", "root", "cj", "pd", "og", "app"]
    # fmt: on
    doc = doclike.doc  # Ensure works on both Doc and Span.
    if not doc.has_annotation("DEP"):
        raise ValueError(Errors.E029)
    np_label = doc.vocab.strings.add("NP")
    np_deps = set(doc.vocab.strings.add(label) for label in labels)
    close_app = doc.vocab.strings.add("nk")
    rbracket = 0
    prev_end = -1
    for i, word in enumerate(doclike):
        if i < rbracket:
            continue
        # Prevent nested chunks from being produced
        if word.left_edge.i <= prev_end:
            continue
        if word.pos in (NOUN, PROPN, PRON) and word.dep in np_deps:
            rbracket = word.i + 1
            # try to extend the span to the right
            # to capture close apposition/measurement constructions
            for rdep in doc[word.i].rights:
                if rdep.pos in (NOUN, PROPN) and rdep.dep == close_app:
                    rbracket = rdep.i + 1
            prev_end = rbracket - 1
            yield word.left_edge.i, rbracket, np_label


SYNTAX_ITERATORS = {"noun_chunks": noun_chunks}