From 4a90c32344a510cdc2b405fc8da31717d909a49e Mon Sep 17 00:00:00 2001 From: Keith Alcock Date: Wed, 4 Dec 2024 23:52:51 -0700 Subject: [PATCH 1/5] Communicate over stdin and stdout --- belief_pipeline/pandas_output_stage.py | 14 +++++++--- belief_pipeline/tpi_habitus.py | 38 ++++++++++++++++++++++++++ belief_pipeline/tpi_input_stage.py | 23 ++++++++++++++-- 3 files changed, 69 insertions(+), 6 deletions(-) create mode 100644 belief_pipeline/tpi_habitus.py diff --git a/belief_pipeline/pandas_output_stage.py b/belief_pipeline/pandas_output_stage.py index 649d98e2..1bc416fa 100644 --- a/belief_pipeline/pandas_output_stage.py +++ b/belief_pipeline/pandas_output_stage.py @@ -1,7 +1,4 @@ from pandas import DataFrame - -# import os - from pipeline import OutputStage class PandasOutputStage(OutputStage): @@ -10,6 +7,15 @@ def __init__(self, file_name: str) -> None: # if not os.path.exists(file_name): # os.makedirs(file_name) # find the directory it's in, not use the entire file + def write(self, text): + nl_count = text.count("\n") + 1 + print(str(nl_count)) + print(text, flush=True) + # keep track of conf_threshold, coref def run(self, data_frame: DataFrame) -> None: - data_frame.to_csv(self.file_name, sep="\t", index=False, encoding="utf-8") + if self.file_name: + data_frame.to_csv(self.file_name, sep="\t", index=False, encoding="utf-8") + else: + text = data_frame.to_csv(self.file_name, sep="\t", index=False, encoding="utf-8") + self.write(text) diff --git a/belief_pipeline/tpi_habitus.py b/belief_pipeline/tpi_habitus.py new file mode 100644 index 00000000..7608ee05 --- /dev/null +++ b/belief_pipeline/tpi_habitus.py @@ -0,0 +1,38 @@ +from argparse import ArgumentParser +from pandas_output_stage import PandasOutputStage +from pipeline import Pipeline +from tpi_belief_stage import TpiBeliefStage +from tpi_input_stage import TpiInputStage +from tpi_location_stage import TpiLocationStage +from tpi_resolution_stage import TpiResolutionStage +from tpi_sentiment_stage import TpiSentimentStage +from typing import Tuple + +import sys + +def get_locations() -> Tuple[str, str]: + argument_parser = ArgumentParser() + argument_parser.add_argument("-l", "--location", required=True, help="location file name") + args = argument_parser.parse_args() + return args.location + +if __name__ == "__main__": + sys.stdin.reconfigure(encoding="utf-8", newline='\n') # just in case! + sys.stdout.reconfigure(encoding="utf-8", newline='\n') # just in case! + + belief_model_name: str = "maxaalexeeva/belief-classifier_mturk_unmarked-trigger_bert-base-cased_2023-4-26-0-34" + sentiment_model_name: str = "hriaz/finetuned_beliefs_sentiment_classifier_experiment1" + locations_file_name: str = get_locations() + pipeline = Pipeline( + TpiInputStage(None), + [ + TpiResolutionStage(), + TpiBeliefStage(belief_model_name), + TpiSentimentStage(sentiment_model_name), + TpiLocationStage(locations_file_name) + ], + PandasOutputStage(None) + ) + + while (True): + pipeline.run() diff --git a/belief_pipeline/tpi_input_stage.py b/belief_pipeline/tpi_input_stage.py index a6e7f191..2e8a7df1 100644 --- a/belief_pipeline/tpi_input_stage.py +++ b/belief_pipeline/tpi_input_stage.py @@ -1,9 +1,11 @@ -from pandas import DataFrame +from io import StringIO from numbers import Number +from pandas import DataFrame from pipeline import InputStage import math import pandas +import sys class TpiInputStage(InputStage): def __init__(self, file_name: str) -> None: @@ -45,8 +47,25 @@ def mk_data_frame(self, file_name: str) -> DataFrame: print("There is an empty sentence!") data_frame["sentence"][index] = "" # What should be done? return data_frame + + def read(self) -> StringIO: + # In Python, the line separator is preserved. + nl_count = int(sys.stdin.readline().strip()) + buffer = StringIO() + for i in range(0, nl_count): + line = sys.stdin.readline() + if i + 1 < nl_count: + buffer.write(line) + else: + # Remove trailing NL from last line. + buffer.write(line[:-1]) + return buffer def run(self) -> DataFrame: - data_frame = self.mk_data_frame(self.file_name) + if self.file_name: + source = self.file_name + else: + source = self.read() + data_frame = self.mk_data_frame(source) # data_frame = data_frame[0:1000] # TODO: remove return data_frame From b69d00cce2cebac02eb524bdf7ef6ceb064d8daa Mon Sep 17 00:00:00 2001 From: Keith Alcock Date: Thu, 5 Dec 2024 16:11:12 -0700 Subject: [PATCH 2/5] Make sure it works with strings --- belief_pipeline/tpi_habitus.py | 19 +++++++++++-------- belief_pipeline/tpi_input_stage.py | 18 ++++++++++++++---- 2 files changed, 25 insertions(+), 12 deletions(-) diff --git a/belief_pipeline/tpi_habitus.py b/belief_pipeline/tpi_habitus.py index 7608ee05..21a602fb 100644 --- a/belief_pipeline/tpi_habitus.py +++ b/belief_pipeline/tpi_habitus.py @@ -10,28 +10,31 @@ import sys -def get_locations() -> Tuple[str, str]: +def get_arguments() -> Tuple[str, str, str]: argument_parser = ArgumentParser() argument_parser.add_argument("-l", "--location", required=True, help="location file name") + argument_parser.add_argument("-i", "--input", required=False, help="input file name") + argument_parser.add_argument("-o", "--output", required=False, help="output file name") args = argument_parser.parse_args() - return args.location + return (args.location, args.input, args.output) if __name__ == "__main__": - sys.stdin.reconfigure(encoding="utf-8", newline='\n') # just in case! - sys.stdout.reconfigure(encoding="utf-8", newline='\n') # just in case! - belief_model_name: str = "maxaalexeeva/belief-classifier_mturk_unmarked-trigger_bert-base-cased_2023-4-26-0-34" sentiment_model_name: str = "hriaz/finetuned_beliefs_sentiment_classifier_experiment1" - locations_file_name: str = get_locations() + locations_file_name, input_file_name, output_file_name = get_arguments() + if not input_file_name: + sys.stdin.reconfigure(encoding="utf-8", newline='\n') # just in case! + if not output_file_name: + sys.stdout.reconfigure(encoding="utf-8", newline='\n') # just in case! pipeline = Pipeline( - TpiInputStage(None), + TpiInputStage(input_file_name), [ TpiResolutionStage(), TpiBeliefStage(belief_model_name), TpiSentimentStage(sentiment_model_name), TpiLocationStage(locations_file_name) ], - PandasOutputStage(None) + PandasOutputStage(output_file_name) ) while (True): diff --git a/belief_pipeline/tpi_input_stage.py b/belief_pipeline/tpi_input_stage.py index 2e8a7df1..088cb32c 100644 --- a/belief_pipeline/tpi_input_stage.py +++ b/belief_pipeline/tpi_input_stage.py @@ -12,8 +12,8 @@ def __init__(self, file_name: str) -> None: super().__init__(".") self.file_name = file_name - def mk_data_frame(self, file_name: str) -> DataFrame: - data_frame = pandas.read_csv(self.file_name, sep="\t", encoding="utf-8", na_values=[""], keep_default_na=False, dtype={ + def mk_data_frame(self, file_name: str, sep: str) -> DataFrame: + data_frame = pandas.read_csv(file_name, sep=sep, encoding="utf-8", na_values=[""], keep_default_na=False, dtype={ "url": str, "terms": str, "date": str, @@ -59,13 +59,23 @@ def read(self) -> StringIO: else: # Remove trailing NL from last line. buffer.write(line[:-1]) - return buffer + value = buffer.getvalue() + return StringIO(value) + + def read2(self) -> StringIO: + with open(self.file_name, "r", encoding="utf-8") as file: + file_content = file.read() + return StringIO(file_content) def run(self) -> DataFrame: if self.file_name: source = self.file_name + sep = "\t" + # source = self.read2() + # sep = "," else: source = self.read() - data_frame = self.mk_data_frame(source) + sep = "," + data_frame = self.mk_data_frame(source, sep) # data_frame = data_frame[0:1000] # TODO: remove return data_frame From 1a526d4e0b342e7fa4875fef24506c89e6dd6159 Mon Sep 17 00:00:00 2001 From: Keith Alcock Date: Fri, 6 Dec 2024 14:46:33 -0700 Subject: [PATCH 3/5] Process calls from Scala --- belief_pipeline/pandas_output_stage.py | 10 ++++++++-- belief_pipeline/tpi_habitus.py | 19 ++++++++++++++++--- belief_pipeline/tpi_input_stage.py | 9 ++++++++- 3 files changed, 32 insertions(+), 6 deletions(-) diff --git a/belief_pipeline/pandas_output_stage.py b/belief_pipeline/pandas_output_stage.py index 1bc416fa..cb5d9302 100644 --- a/belief_pipeline/pandas_output_stage.py +++ b/belief_pipeline/pandas_output_stage.py @@ -7,15 +7,21 @@ def __init__(self, file_name: str) -> None: # if not os.path.exists(file_name): # os.makedirs(file_name) # find the directory it's in, not use the entire file + def log(self, message: str): + with open("output.txt", "a", encoding="utf-8", newline="\n") as file: + print(message, file=file) + def write(self, text): nl_count = text.count("\n") + 1 + self.log(str(nl_count)) print(str(nl_count)) + self.log(text) print(text, flush=True) # keep track of conf_threshold, coref def run(self, data_frame: DataFrame) -> None: if self.file_name: - data_frame.to_csv(self.file_name, sep="\t", index=False, encoding="utf-8") + data_frame.to_csv(self.file_name, sep="\t", index=False, encoding="utf-8", lineterminator="\n") else: - text = data_frame.to_csv(self.file_name, sep="\t", index=False, encoding="utf-8") + text = data_frame.to_csv(self.file_name, sep=",", index=False, encoding="utf-8", lineterminator="\n") self.write(text) diff --git a/belief_pipeline/tpi_habitus.py b/belief_pipeline/tpi_habitus.py index 21a602fb..6d5de690 100644 --- a/belief_pipeline/tpi_habitus.py +++ b/belief_pipeline/tpi_habitus.py @@ -1,3 +1,10 @@ +import os +import sys + +print("Keith was here.", file=sys.stderr) +print("The current directory is ", os.getcwd(), file=sys.stderr) + + from argparse import ArgumentParser from pandas_output_stage import PandasOutputStage from pipeline import Pipeline @@ -12,12 +19,16 @@ def get_arguments() -> Tuple[str, str, str]: argument_parser = ArgumentParser() - argument_parser.add_argument("-l", "--location", required=True, help="location file name") - argument_parser.add_argument("-i", "--input", required=False, help="input file name") - argument_parser.add_argument("-o", "--output", required=False, help="output file name") + argument_parser.add_argument("-l", "--location", required=True, help="location file name") + argument_parser.add_argument("-i", "--input", required=False, help="input file name") + argument_parser.add_argument("-o", "--output", required=False, help="output file name") args = argument_parser.parse_args() return (args.location, args.input, args.output) +def log(message: str): + with open("log.txt", "a", encoding="utf-8", newline="\n") as file: + print(message, file=file) + if __name__ == "__main__": belief_model_name: str = "maxaalexeeva/belief-classifier_mturk_unmarked-trigger_bert-base-cased_2023-4-26-0-34" sentiment_model_name: str = "hriaz/finetuned_beliefs_sentiment_classifier_experiment1" @@ -26,6 +37,7 @@ def get_arguments() -> Tuple[str, str, str]: sys.stdin.reconfigure(encoding="utf-8", newline='\n') # just in case! if not output_file_name: sys.stdout.reconfigure(encoding="utf-8", newline='\n') # just in case! + # TODO: add a way to quiet the output, i.e., to suppress progress bars pipeline = Pipeline( TpiInputStage(input_file_name), [ @@ -37,5 +49,6 @@ def get_arguments() -> Tuple[str, str, str]: PandasOutputStage(output_file_name) ) + log("The program started.") while (True): pipeline.run() diff --git a/belief_pipeline/tpi_input_stage.py b/belief_pipeline/tpi_input_stage.py index 088cb32c..9d408810 100644 --- a/belief_pipeline/tpi_input_stage.py +++ b/belief_pipeline/tpi_input_stage.py @@ -48,12 +48,19 @@ def mk_data_frame(self, file_name: str, sep: str) -> DataFrame: data_frame["sentence"][index] = "" # What should be done? return data_frame + def log(self, message: str): + with open("input.txt", "a", encoding="utf-8", newline="\n") as file: + print(message, file=file) + def read(self) -> StringIO: # In Python, the line separator is preserved. - nl_count = int(sys.stdin.readline().strip()) + line = sys.stdin.readline() + self.log(line) + nl_count = int(line) buffer = StringIO() for i in range(0, nl_count): line = sys.stdin.readline() + self.log(line) if i + 1 < nl_count: buffer.write(line) else: From 170dd91a9ef0bfcb992a29598caa8ef34a589ce4 Mon Sep 17 00:00:00 2001 From: Keith Alcock Date: Wed, 8 Jan 2025 16:14:24 -0700 Subject: [PATCH 4/5] Check in WIP --- belief_pipeline/tpi_habitus.py | 16 +- .../tpi_location_stage_with_patch.py | 145 ++++++++++++++++++ belief_pipeline/vector_vector_stage.py | 1 + 3 files changed, 156 insertions(+), 6 deletions(-) create mode 100644 belief_pipeline/tpi_location_stage_with_patch.py diff --git a/belief_pipeline/tpi_habitus.py b/belief_pipeline/tpi_habitus.py index 6d5de690..9099f9a0 100644 --- a/belief_pipeline/tpi_habitus.py +++ b/belief_pipeline/tpi_habitus.py @@ -1,8 +1,8 @@ -import os -import sys +# import os +# import sys -print("Keith was here.", file=sys.stderr) -print("The current directory is ", os.getcwd(), file=sys.stderr) +# print("Keith was here.", file=sys.stderr) +# print("The current directory is ", os.getcwd(), file=sys.stderr) from argparse import ArgumentParser @@ -10,11 +10,13 @@ from pipeline import Pipeline from tpi_belief_stage import TpiBeliefStage from tpi_input_stage import TpiInputStage -from tpi_location_stage import TpiLocationStage +from tpi_location_stage_with_patch import TpiLocationStage from tpi_resolution_stage import TpiResolutionStage from tpi_sentiment_stage import TpiSentimentStage +from vector_vector_stage import VectorVectorStage from typing import Tuple +import os import sys def get_arguments() -> Tuple[str, str, str]: @@ -32,6 +34,7 @@ def log(message: str): if __name__ == "__main__": belief_model_name: str = "maxaalexeeva/belief-classifier_mturk_unmarked-trigger_bert-base-cased_2023-4-26-0-34" sentiment_model_name: str = "hriaz/finetuned_beliefs_sentiment_classifier_experiment1" + vector_model_name: str = "all-MiniLM-L6-v2" locations_file_name, input_file_name, output_file_name = get_arguments() if not input_file_name: sys.stdin.reconfigure(encoding="utf-8", newline='\n') # just in case! @@ -44,7 +47,8 @@ def log(message: str): TpiResolutionStage(), TpiBeliefStage(belief_model_name), TpiSentimentStage(sentiment_model_name), - TpiLocationStage(locations_file_name) + TpiLocationStage(locations_file_name), + VectorVectorStage(vector_model_name) ], PandasOutputStage(output_file_name) ) diff --git a/belief_pipeline/tpi_location_stage_with_patch.py b/belief_pipeline/tpi_location_stage_with_patch.py new file mode 100644 index 00000000..ac16868e --- /dev/null +++ b/belief_pipeline/tpi_location_stage_with_patch.py @@ -0,0 +1,145 @@ +from pandas import DataFrame +from pipeline import InnerStage +from tqdm import tqdm + +import itertools +import pandas +import re +import spacy + +class TextWithIndices(): + def __init__(self, text, indices=None): + super().__init__() + self.text = text + if indices == None: + self.indices = [index for index, value in enumerate(text)] + else: + self.indices = indices + + def split(self, separator: str) -> list["TextWithIndices"]: + parts = self.text.split(separator) + textWithIndicesList = [] + offset = 0 + for part in parts: + textWithIndices = TextWithIndices(part, self.indices[offset:offset + len(part)]) + textWithIndicesList.append(textWithIndices) + offset += len(part) + offset += len(separator) + return textWithIndicesList + + def re_sub(self, pattern: str, repl: str) -> "TextWithIndices": + done = False + text = self.text + indices = self.indices + while not done: + match = re.search(pattern, text) + if match == None: + done = True + else: + # The indices must be done before the text gets changed. + indices = indices[0:match.start()] + ([-1] * len(repl)) + indices[match.end():len(text)] + text = text[0:match.start()] + repl + text[match.end():len(text)] + return TextWithIndices(text, indices) + + +class Location(): + def __init__(self, textWithIndices: TextWithIndices, lat: float, lon: float, canonical: str, geonameid: str): + # Make sure indices are reasonable. + if -1 in textWithIndices.indices: + print("There is a -1 among the indices!") + for index, offset in enumerate(textWithIndices.indices): + if offset != textWithIndices.indices[0] + index: + print("The indices are not consecutive!") + self.textWithIndices = textWithIndices + self.lat = lat + self.lon = lon + self.canonical = canonical + self.geonameid = geonameid + + def __str__(self): + return f"{self.textWithIndices.text}\t{self.canonical}\t{self.geonameid}\t{self.textWithIndices.indices[0]}\t{self.textWithIndices.indices[-1] + 1}\t{self.lat}\t{self.lon}" + +class TpiLocationStage(InnerStage): + def __init__(self, locations_file_name: str) -> None: + super().__init__() + # The Uganda locations file has an extra column of notes, but we are not using it, so it is not included + # in order to keep the code compatible with the Ghana locations. The extra column causes confusion with + # identification of the index column, so that is explicitly turned off here. You will see a warning + # message on the console about lost data, probably from the extra column that we're not using here: + # ParserWarning: Length of header or names does not match length of data. This leads to a loss of data + # with index_col=False. + locations_data_frame = pandas.read_csv(locations_file_name, sep="\t", encoding="utf-8", index_col=False, names=[ + "geonameid", "name", "asciiname", "alternatenames", "latitude", "longitude", "unk1", "unk2", "country_code", + "cc2", "unk3", "unk4", "unk5", "unk6", "population", "elevation", "unk7", "timezone", "unk8" #, "notes" + ]) + names = locations_data_frame["name"] + ascii_names = locations_data_frame["asciiname"] + alternate_names = locations_data_frame["alternatenames"] + latitudes = locations_data_frame["latitude"] + longitudes = locations_data_frame["longitude"] + geonameids = locations_data_frame["geonameid"] + self.names_to_canonical = self.get_names_to_values(names, ascii_names, alternate_names, names) + self.names_to_latitudes = self.get_names_to_values(names, ascii_names, alternate_names, latitudes) + self.names_to_longitudes = self.get_names_to_values(names, ascii_names, alternate_names, longitudes) + self.names_to_geonameids = self.get_names_to_values(names, ascii_names, alternate_names, geonameids) + # These are real locations in the ghana locations file from geonames (https://download.geonames.org/export/dump/), + # but they also happen to be frequent English words, so we exclude them from being identified as locations. + self.common_words = ["We", "No", "To", "Some"] + self.NER = NER = spacy.load("en_core_web_sm") + + def get_names_to_values(self, names: list[str], ascii_names: list[str], alternate_names: list[str], values: list[str]) -> dict[str, str]: + # In case there are duplicates, these are read from lowest to highest priority, so that the lower ones are overwritten. + names_to_values = {} + for name, value in zip(alternate_names, values): + if type(name) is str: + split = name.split(",") + for item in split: + names_to_values[item] = value + for name, value in zip(names, values): + names_to_values[name] = value + for name, value in zip(ascii_names, values): + names_to_values[name] = value + return names_to_values + + def add_location(self, locations: list[Location], entityWithIndices: TextWithIndices) -> None: + # NER includes `the` in locations, but the location database file doesn't. + # The above sentence is not true, so by removing "the" we could be missing locations. + # TODO: what should be done if this is not the case? There are some instances + # in the database. Should both be checked? Yes, they should indeed. + # However, they were not in the initial pass and we don't want to find locations + # that weren't there before, because that would necessitate reading every sentence + # just in case there was a new one. + # The canonical name should be the one in the database. + # Let's not find any new ones with this. + # entityWithIndices = entityWithIndices.re_sub("^[Tt]he\s", "") + entityWithIndices = entityWithIndices.re_sub("^the\s", "") + if entityWithIndices.text in self.names_to_latitudes and not entityWithIndices.text in self.common_words and entityWithIndices.text[0].isupper(): + location = Location(entityWithIndices, self.names_to_latitudes[entityWithIndices.text], self.names_to_longitudes[entityWithIndices.text], self.names_to_canonical[entityWithIndices.text], self.names_to_geonameids[entityWithIndices.text]) + locations.append(location) + + def get_cell_locations(self, textWithIndices: TextWithIndices) -> list[Location]: + # Replace author citations where possible because they sometimes get labeled as locations. + textWithIndices = textWithIndices.re_sub("[A-Z][a-z]+,\s\d\d\d\d", "(Author, year)") + entities = self.NER(textWithIndices.text).ents + non_persons = [entity for entity in entities if entity.label_ != "PERSON"] + locations = [] + for entity in non_persons: + entitiesWithIndices = TextWithIndices(str(entity), textWithIndices.indices[entity.start_char:entity.end_char]) + entityWithIndicesList = entitiesWithIndices.split(", ") + for entityWithIndices in entityWithIndicesList: + self.add_location(locations, entityWithIndices) + # We need to keep track of multiple, matching locations now. + # However, they should have differing ranges, so the set operation is still OK. + # It would work if only they could actually be compared to each other. + return locations # sorted(list(set(locations))) + + def get_column_locations(self, strings: list[str], desc: str) -> list[str]: + locations_list = [self.get_cell_locations(TextWithIndices(string)) for string in tqdm(strings, desc=f"Finding {desc} locations")] + joined_locations = [", ".join([str(location) for location in locations]) for locations in locations_list] + return joined_locations + + def run(self, data_frame: DataFrame) -> DataFrame: + sentence_locations = self.get_column_locations(data_frame["sentence"], "sentence") + data_frame["sent_locs"] = sentence_locations + data_frame.drop(columns=["context"], inplace=True) + return data_frame diff --git a/belief_pipeline/vector_vector_stage.py b/belief_pipeline/vector_vector_stage.py index ece9336f..2667b104 100644 --- a/belief_pipeline/vector_vector_stage.py +++ b/belief_pipeline/vector_vector_stage.py @@ -25,4 +25,5 @@ def mk_vectors(self, data_frame: DataFrame): def run(self, data_frame: DataFrame) -> DataFrame: vectors = self.mk_vectors(data_frame) data_frame["vector"] = vectors + data_frame.drop(columns=["sentence"], inplace=True) return data_frame From 43b0173e667cf2c7666c6ebb39d40cef25941a79 Mon Sep 17 00:00:00 2001 From: Keith Alcock Date: Tue, 21 Jan 2025 17:15:25 -0700 Subject: [PATCH 5/5] Address NA warning --- belief_pipeline/tpi_input_stage.py | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/belief_pipeline/tpi_input_stage.py b/belief_pipeline/tpi_input_stage.py index 9d408810..7d5f3431 100644 --- a/belief_pipeline/tpi_input_stage.py +++ b/belief_pipeline/tpi_input_stage.py @@ -38,10 +38,14 @@ def mk_data_frame(self, file_name: str, sep: str) -> DataFrame: "effectText": str, "prevSentence": str }) - data_frame["prevSentence"].fillna("", inplace=True) + # data_frame["prevSentence"].fillna("", inplace=True) + # data_frame["prevSentence"] = data_frame["prevSentence"].fillna("") + data_frame.fillna({"prevSentence": ""}, inplace=True) # Sometimes a sentence can be trimmed to empty and considered nan. # This is because of a mismatch in characters considered trimmable. - data_frame["sentence"].fillna("", inplace=True) + # data_frame["sentence"].fillna("", inplace=True) + # data_frame["sentence"] = data_frame["sentence"].fillna("") + data_frame.fillna({"sentence": ""}, inplace=True) for index, sentence in enumerate(data_frame["sentence"]): if sentence == "": # or (isinstance(sentence, Number) and math.isnan(sentence)): print("There is an empty sentence!")