Revise documentation.

Author: hankcs

README.md

@@ -2,7 +2,7 @@
 
 [中文](https://github.com/hankcs/HanLP/tree/doc-zh) |  [docs](https://hanlp.hankcs.com/docs/) | [1.x](https://github.com/hankcs/HanLP/tree/1.x) | [forum](https://bbs.hankcs.com/) | [docker](https://github.com/WalterInSH/hanlp-jupyter-docker)
 
-The multilingual NLP library for researchers and companies, built on PyTorch and TensorFlow 2.x, for advancing state-of-the-art deep learning techniques in both academia and industry. HanLP was designed from day one to be efficient, user friendly and extendable. It comes with pretrained models for 104 human languages including English, Chinese and many others.
+The multilingual NLP library for researchers and companies, built on PyTorch and TensorFlow 2.x, for advancing state-of-the-art deep learning techniques in both academia and industry. HanLP was designed from day one to be efficient, user friendly and extendable.
 
 Thanks to open-access corpora like Universal Dependencies and OntoNotes, HanLP 2.1 now offers 10 joint tasks on 104 languages: tokenization, lemmatization, part-of-speech tagging, token feature extraction, dependency parsing, constituency parsing, semantic role labeling, semantic dependency parsing, abstract meaning representation (AMR) parsing.
 
@@ -45,12 +45,14 @@ HanLPClient HanLP = new HanLPClient("https://hanlp.hankcs.com/api", "your_auth",
 
 ### Quick Start
 
-No matter which language you uses, the same interface can be used to parse a document.
+No matter which language you use, the same interface can be used to parse a document.
 
 ```python
 HanLP.parse("In 2021, HanLPv2.1 delivers state-of-the-art multilingual NLP techniques to production environment. 2021年、HanLPv2.1は次世代の最先端多言語NLP技術を本番環境に導入します。2021年 HanLPv2.1为生产环境带来次世代最先进的多语种NLP技术。")
 ```
 
+See [docs](https://hanlp.hankcs.com/docs/tutorial.html) for visualization, annotation guidelines and more details.
+
 ## Native APIs
 
 ```bash
@@ -63,21 +65,21 @@ HanLP requires Python 3.6 or later. GPU/TPU is suggested but not mandatory.
 
 ```python
 import hanlp
-HanLP = hanlp.load(hanlp.pretrained.mtl.CLOSE_TOK_POS_NER_SRL_DEP_SDP_CON_ELECTRA_SMALL_ZH)
-HanLP(['In 2021, HanLPv2.1 delivers state-of-the-art multilingual NLP techniques to production environment.',
-       '2021年、HanLPv2.1は次世代の最先端多言語NLP技術を本番環境に導入します。',
-       '2021年 HanLPv2.1为生产环境带来次世代最先进的多语种NLP技术。'])
+HanLP = hanlp.load(hanlp.pretrained.mtl.UD_ONTONOTES_TOK_POS_LEM_FEA_NER_SRL_DEP_SDP_CON_MT5_BASE)
+print(HanLP(['In 2021, HanLPv2.1 delivers state-of-the-art multilingual NLP techniques to production environment.',
+            '2021年、HanLPv2.1は次世代の最先端多言語NLP技術を本番環境に導入します。',
+            '2021年 HanLPv2.1为生产环境带来次世代最先进的多语种NLP技术。']))
 ```
 
-In particular, the Python `HanLPClient` can also be used as a callable function following the same semantics. See [docs](https://hanlp.hankcs.com/docs/) for more details.
+In particular, the Python `HanLPClient` can also be used as a callable function following the same semantics. See [docs](https://hanlp.hankcs.com/docs/tutorial.html) for visualization, annotation guidelines and more details.
 
 ## Train Your Own Models
 
 To write DL models is not hard, the real hard thing is to write a model able to reproduce the scores in papers. The snippet below shows how to surpass the state-of-the-art tokenizer in 9 minutes.
 
 ```python
 tokenizer = TransformerTaggingTokenizer()
-save_dir = 'data/model/cws/sighan2005_pku_bert_base_96.61'
+save_dir = 'data/model/cws/sighan2005_pku_bert_base_96.66'
 tokenizer.fit(
     SIGHAN2005_PKU_TRAIN_ALL,
     SIGHAN2005_PKU_TEST,  # Conventionally, no devset is used. See Tian et al. (2020).
@@ -97,13 +99,13 @@ tokenizer.fit(
 tokenizer.evaluate(SIGHAN2005_PKU_TEST, save_dir)
 ```
 
-The result is guaranteed to be `96.66` as the random feed is fixed. Different from some overclaining papers and projects, HanLP promises every digit in our scores are reproducible. Any issues on reproducibility will be treated and solved as a top-priority fatal bug.
+The result is guaranteed to be `96.66` as the random feed is fixed. Different from some overclaiming papers and projects, HanLP promises every single digit in our scores is reproducible. Any issues on reproducibility will be treated and solved as a top-priority fatal bug.
 
 ## Performance
 
 <table><thead><tr><th rowspan="2">lang</th><th rowspan="2">corpora</th><th rowspan="2">model</th><th colspan="2">tok</th><th colspan="4">pos</th><th colspan="3">ner</th><th rowspan="2">dep</th><th rowspan="2">con</th><th rowspan="2">srl</th><th colspan="4">sdp</th><th rowspan="2">lem</th><th rowspan="2">fea</th><th rowspan="2">amr</th></tr><tr><td>fine</td><td>coarse</td><td>ctb</td><td>pku</td><td>863</td><td>ud</td><td>pku</td><td>msra</td><td>ontonotes</td><td>SemEval16</td><td>DM</td><td>PAS</td><td>PSD</td></tr></thead><tbody><tr><td rowspan="2">mul</td><td rowspan="2">UD2.7 <br>OntoNotes5</td><td>small</td><td>98.30</td><td>-</td><td>-</td><td>-</td><td>-</td><td>91.72</td><td>-</td><td>-</td><td>74.86</td><td>74.66</td><td>74.29</td><td>65.73</td><td>-</td><td>88.52</td><td>92.56</td><td>83.84</td><td>84.65</td><td>81.13</td><td>-</td></tr><tr><td>base</td><td>99.59</td><td>-</td><td>-</td><td>-</td><td>-</td><td>95.95</td><td>-</td><td>-</td><td>80.31</td><td>85.84</td><td>80.22</td><td>74.61</td><td>-</td><td>93.23</td><td>95.16</td><td>86.57</td><td>92.91</td><td>90.30</td><td>-</td></tr><tr><td rowspan="4">zh</td><td rowspan="2">open</td><td>small</td><td>97.25</td><td>-</td><td>96.66</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>95.00</td><td>84.57</td><td>87.62</td><td>73.40</td><td>84.57</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>base</td><td>97.50</td><td>-</td><td>97.07</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>96.04</td><td>87.11</td><td>89.84</td><td>77.78</td><td>87.11</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td rowspan="2">close</td><td>small</td><td>96.70</td><td>95.93</td><td>96.87</td><td>97.56</td><td>95.05</td><td>-</td><td>96.22</td><td>95.74</td><td>76.79</td><td>84.44</td><td>88.13</td><td>75.81</td><td>74.28</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>base</td><td>97.52</td><td>96.44</td><td>96.99</td><td>97.59</td><td>95.29</td><td>-</td><td>96.48</td><td>95.72</td><td>77.77</td><td>85.29</td><td>88.57</td><td>76.52</td><td>73.76</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr></tbody></table>
 
-- Multilingual models are temporary ones which will be replaced in one week.
+- Multilingual models are temporary which will be replaced in one week.
 - AMR models will be released once our paper gets accepted.
 
 ## Citing
@@ -127,7 +129,7 @@ HanLP is licensed under **Apache License 2.0**. You can use HanLP in your commer
 
 ### Models
 
-Unless specified, all models in HanLP are licensed under  [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) . 
+Unless otherwise specified, all models in HanLP are licensed under  [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/). 
 
 ## References
 

docs/configure.md

@@ -51,3 +51,11 @@ environment variable and HanLP will pick it up at the next startup.
 export HANLP_URL=http://mirrors-hk.miduchina.com/hanlp/
 ```
 
+## Control Verbosity
+
+By default, HanLP will print progressive message to console when you load a model. If you want to silence it, use the 
+following environment variable.
+
+```bash
+export HANLP_VERBOSE=0
+```

docs/tutorial.md

@@ -53,7 +53,7 @@ print(HanLP('In 2021, HanLPv2.1 delivers state-of-the-art multilingual NLP techn
             '2021年、HanLPv2.1は次世代の最先端多言語NLP技術を本番環境に導入します。' \
             '2021年 HanLPv2.1为生产环境带来次世代最先进的多语种NLP技术。'))
 ```
-````{margin} **But what does these annotations mean?**
+````{margin} **But what do these annotations mean?**
 ```{seealso}
 See our [data format](data_format) and [annotations](annotations/index) for details.
 ```
@@ -63,8 +63,8 @@ See our [data format](data_format) and [annotations](annotations/index) for deta
 ## Visualization
 
 ```{eval-rst}
-:class:`~hanlp_common.document.Document` has a handy method :meth:`~hanlp_common.document.Document.pretty_print` 
-which offsers visualization in any mono-width text environment. 
+The returned :class:`~hanlp_common.document.Document` has a handy method :meth:`~hanlp_common.document.Document.pretty_print` 
+which offers visualization in any mono-width text environment. 
 ```
 
 ````{margin} **Non-ASCII**

hanlp/version.py

@@ -2,5 +2,5 @@
 # Author: hankcs
 # Date: 2019-12-28 19:26
 
-__version__ = '2.1.0-alpha.0'
+__version__ = '2.1.0-alpha.2'
 """HanLP version"""