ppsingh commited on
Commit
b1c0107
1 Parent(s): 116679b

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +10 -27
README.md CHANGED
@@ -48,30 +48,13 @@ Specifications
48
  - **response_words(type:list[words])**:Tokens/Words from ResponseText (stopwords not considered)
49
  - **context_wordcount (type:list[int])**: Number of tokens/words in each context (remember context itself is list of multiple strings, and stopwords not considered)
50
  - **strategy (type:str)**: Can take either of *small,medium,large* value. Represents the length of paragraphs/textchunk considered for finding the right context for ResponseText
51
- -
52
- "match_onresponse": [
53
- 0.86,
54
- 0.86,
55
- 0.71
56
- ],
57
- "candidate": [
58
- The list of Sectors covered include: Agriculture', 'Coastal Zone', 'Cross-Cutting Area', 'Education', 'Energy', 'Environment', 'Water', 'Buildings', 'Economy-wide', 'Industries', 'Transport', 'Waste', 'Health', 'LULUCF/Forestry', 'Social Development', 'Disaster Risk Management (DRM)', 'Urban','Tourism'.
59
- Some of the important question categories pertaining to climate change(adapted from climatewatchdata) include
60
- - Sectoral Policies
61
- - Sectoral Unconditional Actions
62
- - Building on existing downstream actions
63
- - Sectoral plans
64
- - Sectoral targets
65
- - Action and priority
66
- - Adapt Now sector
67
- - Emission reduction potential
68
- - Capacity Building Needs for Sectoral Implementation
69
- - Sectoral Conditional Actions
70
- - Technology Transfer Needs for Sectoral Implementation
71
- - Conditional part of mitigation target
72
- - Capacity building needs
73
- - Technology needs
74
- - Unconditional part of mitigation target
75
- - Time frame
76
- - Emission reduction potential
77
- No answer category like 'Squad2' is not part of dataset but can be easily curated from existing examples.
 
48
  - **response_words(type:list[words])**:Tokens/Words from ResponseText (stopwords not considered)
49
  - **context_wordcount (type:list[int])**: Number of tokens/words in each context (remember context itself is list of multiple strings, and stopwords not considered)
50
  - **strategy (type:str)**: Can take either of *small,medium,large* value. Represents the length of paragraphs/textchunk considered for finding the right context for ResponseText
51
+ - **match_onresponse (type:list[float])**: Percentage of overlapping words between Response and context with respect to the length of ResponseText.
52
+ - **candidate (type:list[list[int]])**: Candidate within context which corresponds (fuzzy matching/similarity) to ResponseText. Value at index(0,1) represents (start,end) of string within context
53
+ - **fetched_text (type:list[str])**: Candidate within context which corresponds (fuzzy matching/similarity) to ResponseText.
54
+ - **response_translated(type:str)**:Translated ResponseText
55
+ - **context_translated(type:str)**: Translated Context
56
+ - **candidate_translated(type:str)**: Translated Candidate index values (check column 'candidate')
57
+ - **fetched_text_translated(type:str)**: Translated Candidates (check column 'candidate')
58
+ - **QA_data(type:dict)**: Metadata about ResponseText, highlighting nature of query to which ResponseText corresponds as 'answer/response'
59
+ - **match_onanswer (type:list[float])**: Represents percentage match between Response and candidate text ( from statistics it is recommended to keep only values above 0.3% as
60
+ - answer and consider the context for 'No answer' for SQUAD2 data format)