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open(file_path, 'r', encoding='utf-8') as file: for line in file: - line = line.strip().split('\t') - data.append(line) + line = line.strip().split('\t') # Rozdziel linie na elementy za pomocą tabulatora + data.append(line) # Dodaj elementy do listy danych return data @@ -87,16 +87,40 @@ for line in corpus[:100000]: dictionary.update([word1, word2, word3, word4]) -# In[10]: +# In[15]: -model2 = model.copy() +from collections import defaultdict +from nltk import trigrams +from nltk.tokenize import word_tokenize + +model_trigram = defaultdict(lambda: defaultdict(float)) +dictionary_trigram = set() +for line in corpus[:100000]: + tokens = word_tokenize(line) + for word1, word2, word3 in trigrams(tokens, pad_right=True, pad_left=True): + if word1 and word2 and word3: + model_trigram[(word2, word3)][word1] += 1 + model_trigram[(word1, word2)][word3] += 1 + dictionary_trigram.update([word1, word2, word3]) -# In[ ]: +# In[18]: -len(model) +from collections import defaultdict +from nltk import bigrams +from nltk.tokenize import word_tokenize + +model_bigram = defaultdict(lambda: defaultdict(float)) +dictionary_bigram = set() +for line in corpus[:100000]: + tokens = word_tokenize(line) + for word1, word2 in bigrams(tokens, pad_right=True, pad_left=True): + if word1 and word2: + model_bigram[word2][word1] += 1 + model_bigram[word1][word2] += 1 + dictionary_bigram.update([word1, word2]) # In[11]: @@ -109,7 +133,27 @@ for trio in model: model[trio][token] = (model[trio][token] + smoothing) / count_sum -# In[12]: +# In[17]: + + +smoothing = 0.0001 +for trio in model_trigram: + count_sum = sum(model_trigram[trio].values()) + smoothing * len(dictionary_trigram) + for token in model_trigram[trio]: + model_trigram[trio][token] = (model_trigram[trio][token] + smoothing) / count_sum + + +# In[19]: + + +smoothing = 0.0001 +for trio in model_bigram: + count_sum = sum(model_bigram[trio].values()) + smoothing * len(dictionary_bigram) + for token in model_bigram[trio]: + model_bigram[trio][token] = (model_bigram[trio][token] + smoothing) / count_sum + + +# In[21]: from collections import Counter @@ -126,21 +170,36 @@ for i in range(len(data)): with open("dev-0\\out.tsv", "w", encoding="utf-8") as output: for text in corpus_before: tokens = word_tokenize(text) - if len(tokens) < 4: - prediction = default + prediction = "" - results = dict(model[(tokens[0], tokens[1], tokens[2])]) - if not results: - prediction = default + if len(tokens) >= 4: + results = dict(model[(tokens[0], tokens[1], tokens[2])]) + if results: + prediction = ' '.join(f"{term}:{round(prob, 5)}" for term, prob in Counter(results).most_common(6)) + + if prediction == "": + trigram_results = dict(model_trigram[(tokens[0], tokens[1])]) + if trigram_results: + prediction = ' '.join(f"{term}:{round(prob, 5)}" for term, prob in Counter(trigram_results).most_common(6)) + + if prediction == "": + bigram_results = dict(model_bigram[tokens[0]]) + if bigram_results: + prediction = ' '.join(f"{term}:{round(prob, 5)}" for term, prob in Counter(bigram_results).most_common(6)) - prediction = ' '.join( - f"{term}:{round(prob, 5)}" for term, prob in Counter(results).most_common(6)) if prediction == "": prediction = default + output.write(str(prediction.replace("\n", "").strip() + "\n")) -# In[13]: +# In[ ]: + + + + + +# In[23]: from collections import Counter @@ -157,17 +216,26 @@ for i in range(len(data)): with open("test-A\\out.tsv", "w", encoding="utf-8") as output: for text in corpus_before: tokens = word_tokenize(text) - if len(tokens) < 4: - prediction = default + prediction = "" - results = dict(model[(tokens[0], tokens[1], tokens[2])]) - if not results: - prediction = default + if len(tokens) >= 4: + results = dict(model[(tokens[0], tokens[1], tokens[2])]) + if results: + prediction = ' '.join(f"{term}:{round(prob, 5)}" for term, prob in Counter(results).most_common(6)) + + if prediction == "": + trigram_results = dict(model_trigram[(tokens[0], tokens[1])]) + if trigram_results: + prediction = ' '.join(f"{term}:{round(prob, 5)}" for term, prob in Counter(trigram_results).most_common(6)) + + if prediction == "": + bigram_results = dict(model_bigram[tokens[0]]) + if bigram_results: + prediction = ' '.join(f"{term}:{round(prob, 5)}" for term, prob in Counter(bigram_results).most_common(6)) - prediction = ' '.join( - f"{term}:{round(prob, 5)}" for term, prob in Counter(results).most_common(6)) if prediction == "": prediction = default + output.write(str(prediction.replace("\n", "").strip() + "\n")) diff --git a/test-A/out.tsv b/test-A/out.tsv index ac5d81f..b183fb5 100644 --- a/test-A/out.tsv +++ b/test-A/out.tsv @@ -1,26 +1,26 @@ -the:0.30000 of:0.20000 and:0.10000 to:0.10000 in:0.10000 a:0.10000 :0.10000 -the:0.30000 of:0.20000 and:0.10000 to:0.10000 in:0.10000 a:0.10000 :0.10000 +the:0.04715 ``:0.01347 beautifully:0.00674 white:0.00674 at:0.00674 and:0.00674 +he:0.08716 i:0.03948 they:0.03318 have:0.02457 right:0.02163 ,:0.0189 ``:0.00744 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