-
_
-
A
- accuracy (3.2)
- address (4.5)
- adjectives (2.6)
- adverbs (2.6)
- agreement (1.1)
- alphabetic variants (4.2)
- anaphora resolution (5.2)
- anaphoric antecedent (5.1)
- antecedent (5.2)
- antonymy (5.3)
- appending (2.1)
- appropriate (5)
- argument (2)
- arity (3.3)
- articles (2.6)
- assignment (3.5)
- associative array (3)
- assumption (2)
- atomic (1.3)
- attribute value matrix (1.3)
- auxiliaries (3.3)
- auxiliary (1.3)
-
B
-
C
- call-by-value (4.4.2)
- call (1.4)
- call structure (4.7.3)
- Catalan numbers (6.2)
- characteristic function (3.4)
- chart (4.4)
- chart parsing (4.4)
- child (4.2)
- chink (2.5)
- chink (8)
- chunk grammar (2.1)
- chunk (2)
- chunking (2)
- class label (1)
- Classification (1)
- closed class (7.4)
- closed (3.1)
- closures (3.4.2)
- code point (3.3.1)
- coindex (2)
- collocation (3.3)
- comparative wordlist (4.3)
- complements (5.1)
- complete (9)
- complex (1.3)
- complex types (3.1)
- components (5.5)
- concatenation (3.2.1)
- conclusion (2)
- conditional expression (4.3)
- conditional frequency distribution (2)
- conditional (6.3)
- confusion matrix (3.4)
- consecutive classification (1.6)
- consistent (1.2)
- constituent (2.1)
- constituent structure (2.1)
- control (4)
- control structure (4.3)
- Cooper storage (4.5)
- coordinate structure (2.1)
- copy (4.1.1)
- coreferential (3.1)
- corpora (0)
- Corpus Linguistics (7)
- cross-validation (3.5)
-
D
- data intensive (I)
- debugger (4.6.4)
- decision nodes (4)
- decision stump (4)
- decision tree (4)
- decoding (3.3.1)
- defensive programming (4.4.4)
- dependents (5)
- determiners (2.6)
- dev-test (1.2)
- development set (1.2)
- dialogue acts (2.2)
- dictionary (3)
- dictionary (3.2)
- directed acyclic graphs (2)
- discourse (5)
- discourse referents (5.1)
- discourse representation structure (5.1)
- dispersion plot (1.3)
- divide-and-conquer (4.7)
- docstring (4.4)
- doctest block (4.4.6)
- domain (3.4)
- DRS conditions (5.1)
- duck typing (4.3)
- dynamic programming (4.4)
-
E
-
F
- F-Measure (3.3)
- F-Score (3.3)
- f-structure (5)
- False negatives (3.3)
- False positives (3.3)
- feature extractor (1.1)
- feature (1.2)
- feature path (2)
- feature set (1.1)
- feature structures (1)
- features (1.1)
- fields (4.2.2)
- filler (3.4)
- folds (3.5)
- formal language theory (I)
- format string (3.9.2)
- free (3.1)
- frequency distribution (3.1)
- function (3.2)
-
G
-
H
-
I
- idealism (II)
- identifiers (2.3)
- immediate constituents (2.1)
- immutable (4.2.2)
- inconsistent (1.2)
- indented code block (1.4)
- independence assumption (5.1)
- index (2.2)
- inference (2)
- Information Extraction (1)
- information gain (4.1)
- Inline annotation (3.5)
- interpreter (1.1)
- IOB tags (2.6)
- iterative optimization (6)
-
J
-
K
-
L
- lambda expressions (4.5.1)
- latent semantic analysis (4.8.4)
- leaf nodes (4)
- left-corner (4.3)
- left-corner parser (4.3)
- left-recursive (3.3)
- lemma (4)
- letter trie (4.7.1)
- lexical acquisition (9)
- lexical categories (0)
- lexical entry (4)
- lexical relations (5.3)
- lexicon (10)
- LGB rule (4.4.3)
- library (3.3)
- licensed (3.4)
- likelihood ratios (1.1)
- Linear-Chain Conditional Random Field Models (1.7)
- list (2.1)
- local variables (3.2)
- logical constants (3.1)
- logical form (2)
-
M
- machine translation (5.3)
- mapping (3)
- maximal projection (3.2)
- Maximum Entropy (6)
- Maximum Entropy Markov Models (1.7)
- Maximum Entropy principle (6.2)
- meronyms (5.3)
- methods (3.2)
- modals (2.6)
- model checking (3.5)
- model (1.2)
- models (7)
- module (3.3)
- morpho-syntactic (7.5)
- morphological analysis (7.5)
- multiword expression (3.11)
- mutable (4.2.2)
-
N
- n-gram tagger (5.3)
- naive Bayes assumption (5.1)
- naive Bayes (5)
- named entity detection (1.1)
- named entity recognition (5)
- newlines (3.1.5)
- NLTK Data Repository (6.3)
- non-logical constants (3.1)
- non-standard words (3.6.2)
- normalized (3.6)
- noun phrase chunking (2.1)
- noun phrase (II)
- NP-chunking (2.1)
-
O
-
P
- package (3.3)
- parameter (1.4)
- parameters (5.5)
- parent (4.2)
- parser (4)
- part-of-speech tagging (0)
- partial information (2.1)
- parts of speech (0)
- personal pronouns (2.6)
- phonology (I)
- phrasal level (3.2)
- POS-tagger (1)
- POS-tagging (0)
- pre-sort (4.7)
- Precision (3.3)
- precision/recall trade-off (5.3)
- predicates (3.1)
- prepositional phrase attachment ambiguity (3.1)
- prepositional phrase (2.1)
- present participle (7.1)
- principle of compositionality (I)
- prior probability (5)
- probabilistic context free grammar (6.3)
- productions (1.1)
- projective (5)
- proof goal (3.2)
- Propositional logic (2)
- propositional symbols (2)
- prune (4.1)
-
Q
-
R
- rationalism (II)
- raw string (3.4.2)
- realism (II)
- Recall (3.3)
- recognizing (4.4)
- record (4.2.2)
- recursion (4.7.1)
- recursive (3.3)
- reduce (4.2)
- reentrancy (2)
- refactor (4.4.5)
- regression testing (4.6.5)
- relation detection (1.1)
- relational operators (4.1)
- replacement field (3.9.2)
- return value (3.2)
- root element (4.3)
- root node (4)
- runtime error (2.2)
-
S
- S-Retrieval (4.5)
- satisfies (3.5)
- scope (3.7)
- segmentation (3.8)
- semantic role labeling (5.2)
- sequence classifier (1.6)
- sequence (3.2.6)
- shift (4.2)
- shift-reduce parser (4.2)
- siblings (4.2)
- signature (3.1)
- slash categories (3.4)
- slicing (2.2)
- smoothing (5.2)
- stack trace (4.6.4)
- standoff annotation (2.3)
- standoff annotation (3.5)
- start-symbol (3.1)
- stopwords (4.1)
- string formatting (3.9.2)
- string (3.2)
- strings (2.4)
- structurally ambiguous (3.1)
- structure sharing (2)
- structured data (1)
- stylistics (1.3)
- subcategorized (5.1)
- subsumption (2.1)
- subtype (5)
- supervised (1)
- Swadesh wordlists (4.3)
- symbolic logic (I)
- synonyms (5.1)
- synset (5.1)
- syntax error (1.1)
-
T
- T9 (3.4.2)
- tag (2)
- tag patterns (2.2)
- tagged (2.2)
- tagging (0)
- tagset (0)
- terms (3.1)
- test set (1.1)
- test set (3.1)
- text alignment (5.4)
- textonyms (3.4.2)
- token (1.4)
- tokenization (3.1.1)
- top-down (4.7.3)
- top-down parsing (4.1)
- total likelihood (6)
- train (5.1)
- training (5.1)
- training set (1.1)
- training set (1.2)
- transitive verbs (5.1)
- tree (4.2)
- True negatives (3.3)
- True positives (3.3)
- truth-conditions (2)
- tuple (4.2)
- Turing Test (5.5)
- Type I errors (3.3)
- Type II errors (3.3)
- type-raising (4.3)
- Typed feature structures (5)
- types (3.1)
-
U
-
V
-
W
-
X
-
Z
-
Α
-
Β
-
Λ
针对 NLTK 3.0 作出更新。本章来自于《Python 自然语言处理》,Steven Bird, Ewan Klein 和 Edward Loper,Copyright © 2014 作者所有。本章依据 Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License 条款,与自然语言工具包 3.0 版一起发行。
本文档构建于星期三 2015 年 7 月 1 日 12:30:05 AEST