def test_annotated_empty(self):
anno_json = corpus.TermLabels(
"../../data/test/samples_with_manual_annotation.json1")
check_corpus = corpus.Corpus(
"../../data/test/samples_news_clean_random.xml",
annotations=anno_json)
self.assertEqual(len(check_corpus), 0)
def test_subsetting(self):
check_corpus = corpus.Corpus(
"../../data/test/samples_news_clean_random.xml")
sample_urls = [
"https://theloadstar.com/will-digitisation-kill-off-forwarder/",
"https://theloadstar.com/alert-airlines-unsafe-hoverboards-iata-calls-stiff-penalty-shippers-mis-declare-battery-devices/",
"https://theloadstar.com/australian-box-terminal-operators-offset-falling-volumes-by-hiking-fees/",
]
subset_xml = check_corpus.get_documents_by_urls(sample_urls)
self.assertEqual(len(subset_xml), len(sample_urls))
def process_manual_annotation():
log.info(
f"Begin incorporating manual annotation to the XML, result in {RELEVANT_DIR}"
)
anno_json = corpus.TermLabels(
os.path.join(MANUAL_DIR, "terms", "news.jsonl"))
manual_corpus = corpus.Corpus(os.path.join(PROCESSED_DIR,
"lda_sampling_15p.xml"),
annotations=anno_json)
manual_corpus.write_xml_to(
os.path.join(PROCESSED_DIR, "lda_sampling_15p.annotated.xml"))
def preprocess_corpus():
log.info(f"Begin combining from {SCRAPED_DIR}")
combined_corpus = corpus.Corpus(SCRAPED_DIR)
log.info("Begin filtering empty documents")
combined_corpus.filter_empty()
n_sample = 10
log.info(f"Begin sampling, n={n_sample}")
sampled_corpus = combined_corpus.get_sample(n_sample)
log.info(f"Write sample.xml to {INTERIM_DIR}")
sampled_corpus.write_xml_to(os.path.join(
INTERIM_DIR, "sample.xml")) # use dummy filename for now
def evaluate_terms():
annotated_corpus = corpus.Corpus(os.path.join(RELEVANT_DIR, "dev.xml"))
log.info("Begin evaluation")
evaluator = evaluation.Evaluator(annotated_corpus)
extracted_terms = {
"TF-IDF": "tfidf.csv",
"KPM": "kpm.csv",
"YAKE": "yake.csv",
"SingleRank": "singlerank.csv",
"TopicRank": "topicrank.csv",
"MultipartiteRank": "mprank.csv",
"PositionRank": "positionrank.csv",
"EmbedRank": "embedrank_wiki_unigrams.csv"
}
for method, file_name in extracted_terms.items():
t = terms.TermsExtractor.read_terms_from(
os.path.join(EXTRACTED_DIR, file_name))
evaluator.add_prediction(method, t)
today_date = date.today().strftime("%Y%m%d")
evaluator.evaluate_and_visualize(
os.path.join(PLOT_DIR, f"eval_{today_date}.html"))
def create_core_nlp_documents(core_nlp_folder):
log.info(f"Begin preparing Core NLP Documents to {core_nlp_folder}")
annotated_corpus = corpus.Corpus(
os.path.join(PROCESSED_DIR, "lda_sampling_15p.annotated.xml"))
annotated_corpus.write_to_core_nlp_xmls(core_nlp_folder)
def test_news(self):
check_corpus1 = corpus.Corpus("../../data/test/samples_news_raw.xml")
self.assertEqual(len(check_corpus1), 2)
def test_combine_and_filter(self):
combined_corpus = corpus.Corpus(
xml_input="../../data/test/scrape_samples/")
self.assertEqual(len(combined_corpus), 102)
combined_corpus.filter_empty()
self.assertEqual(len(combined_corpus), 99)
def test_sampling(self):
check_corpus = corpus.Corpus(
"../../data/test/samples_news_clean_random.xml")
sample_xml = check_corpus.get_sample(3)
self.assertEqual(len(sample_xml), 3)
def test_wiki(self):
check_corpus = corpus.Corpus("../../data/test/samples_wiki.xml")
self.assertEqual(len(check_corpus), 3)
def test_existing_annotation_w_extra_annotation(self):
anno_json = corpus.TermLabels(
"../../data/test/samples_with_manual_annotation.json1")
check_corpus = corpus.Corpus("../../data/test/samples_with_terms.xml",
annotations=anno_json)
self.assertEqual(len(check_corpus), 2)
def test_existing_annotation(self):
check_corpus = corpus.Corpus("../../data/test/samples_with_terms.xml")
self.assertEqual(len(check_corpus), 2)
