Natural Language Processing · 免费预览
用于标注的隐马尔可夫模型
词类与标签集,将标注和命名实体识别视为序列标注,马尔可夫链,HMM 转移概率与发射概率,以及带回溯指针的维特比解码。
1. Hidden Markov Models for Tagging
Hidden Markov Models for Tagging
2. From Markov chains to Viterbi
From Markov chains to Viterbi
3. Training and decoding a tiny tagger
Training and decoding a tiny tagger
4. Sorting the classes
Which grouping of parts of speech into open and closed classes is right?
5. Tags for a small entity set
A BIO tagging scheme covers entity types. How many distinct tags does the per-token labeler output? Answer with the number.
6. Reading the two tables
In an HMM tagger, what do the A and B tables contain, and how are they estimated?
7. One Viterbi cell by hand
At the previous column two states have Viterbi values and . The transitions into the current state are and , and the emission probability of the current observation in state is . Compute , the new cell's Viterbi value, rounding to four decimals.
8. The cost of decoding
A tagger has tags and a sentence of words. How many cells does the Viterbi lattice fill, and how many complete taggings would exhaustive search examine? Give the number of lattice cells (a single number).