📄 Ledgar¶
LEDGAR dataset aims contract provision (paragraph) classification. The contract provisions come from contracts obtained from the US Securities and Exchange Commission (SEC) filings, which are publicly available from EDGAR. Each label represents the single main topic (theme) of the corresponding contract provision… See the full description on the dataset page: https://huggingface.co/datasets/coastalcph/lex_glue.
Tags: annotations_creators:found, arxiv:['2110.00976', '2109.00904', '1805.01217', '2104.08671'], language:en, language_creators:found, license:cc-by-4.0, multilinguality:monolingual, region:us, size_categories:10K<n<100K, source_datasets:extended, task_categories:['question-answering', 'text-classification'], task_ids:['multi-class-classification', 'multi-label-classification', 'multiple-choice-qa', 'topic-classification'], category:dataset
cards.ledgar
type: TaskCard
loader:
type: LoadHF
path: lex_glue
name: ledgar
preprocess_steps:
- type: MapInstanceValues
mappers:
label:
0: Adjustments
1: Agreements
2: Amendments
3: Anti-Corruption Laws
4: Applicable Laws
5: Approvals
6: Arbitration
7: Assignments
8: Assigns
9: Authority
10: Authorizations
11: Base Salary
12: Benefits
13: Binding Effects
14: Books
15: Brokers
16: Capitalization
17: Change In Control
18: Closings
19: Compliance With Laws
20: Confidentiality
21: Consent To Jurisdiction
22: Consents
23: Construction
24: Cooperation
25: Costs
26: Counterparts
27: Death
28: Defined Terms
29: Definitions
30: Disability
31: Disclosures
32: Duties
33: Effective Dates
34: Effectiveness
35: Employment
36: Enforceability
37: Enforcements
38: Entire Agreements
39: Erisa
40: Existence
41: Expenses
42: Fees
43: Financial Statements
44: Forfeitures
45: Further Assurances
46: General
47: Governing Laws
48: Headings
49: Indemnifications
50: Indemnity
51: Insurances
52: Integration
53: Intellectual Property
54: Interests
55: Interpretations
56: Jurisdictions
57: Liens
58: Litigations
59: Miscellaneous
60: Modifications
61: No Conflicts
62: No Defaults
63: No Waivers
64: Non-Disparagement
65: Notices
66: Organizations
67: Participations
68: Payments
69: Positions
70: Powers
71: Publicity
72: Qualifications
73: Records
74: Releases
75: Remedies
76: Representations
77: Sales
78: Sanctions
79: Severability
80: Solvency
81: Specific Performance
82: Submission To Jurisdiction
83: Subsidiaries
84: Successors
85: Survival
86: Tax Withholdings
87: Taxes
88: Terminations
89: Terms
90: Titles
91: Transactions With Affiliates
92: Use Of Proceeds
93: Vacations
94: Venues
95: Vesting
96: Waiver Of Jury Trials
97: Waivers
98: Warranties
99: Withholdings
- type: Set
fields:
classes:
- Adjustments
- Agreements
- Amendments
- Anti-Corruption Laws
- Applicable Laws
- Approvals
- Arbitration
- Assignments
- Assigns
- Authority
- Authorizations
- Base Salary
- Benefits
- Binding Effects
- Books
- Brokers
- Capitalization
- Change In Control
- Closings
- Compliance With Laws
- Confidentiality
- Consent To Jurisdiction
- Consents
- Construction
- Cooperation
- Costs
- Counterparts
- Death
- Defined Terms
- Definitions
- Disability
- Disclosures
- Duties
- Effective Dates
- Effectiveness
- Employment
- Enforceability
- Enforcements
- Entire Agreements
- Erisa
- Existence
- Expenses
- Fees
- Financial Statements
- Forfeitures
- Further Assurances
- General
- Governing Laws
- Headings
- Indemnifications
- Indemnity
- Insurances
- Integration
- Intellectual Property
- Interests
- Interpretations
- Jurisdictions
- Liens
- Litigations
- Miscellaneous
- Modifications
- No Conflicts
- No Defaults
- No Waivers
- Non-Disparagement
- Notices
- Organizations
- Participations
- Payments
- Positions
- Powers
- Publicity
- Qualifications
- Records
- Releases
- Remedies
- Representations
- Sales
- Sanctions
- Severability
- Solvency
- Specific Performance
- Submission To Jurisdiction
- Subsidiaries
- Successors
- Survival
- Tax Withholdings
- Taxes
- Terminations
- Terms
- Titles
- Transactions With Affiliates
- Use Of Proceeds
- Vacations
- Venues
- Vesting
- Waiver Of Jury Trials
- Waivers
- Warranties
- Withholdings
type_of_class: contractual clauses
task: tasks.classification.multi_class
templates: templates.classification.multi_class.all
[source]Explanation about TaskCard¶
TaskCard delineates the phases in transforming the source dataset into model input, and specifies the metrics for evaluation of model output.
- Args:
- loader:
specifies the source address and the loading operator that can access that source and transform it into a unitxt multistream.
- preprocess_steps:
list of unitxt operators to process the data source into model input.
- task:
specifies the fields (of the already (pre)processed instance) making the inputs, the fields making the outputs, and the metrics to be used for evaluating the model output.
- templates:
format strings to be applied on the input fields (specified by the task) and the output fields. The template also carries the instructions and the list of postprocessing steps, to be applied to the model output.
- default_template:
a default template for tasks with very specific task dataset specific template
Explanation about LoadHF¶
Loads datasets from the HuggingFace Hub.
It supports loading with or without streaming, and it can filter datasets upon loading.
- Args:
- path:
The path or identifier of the dataset on the HuggingFace Hub.
- name:
An optional dataset name.
- data_dir:
Optional directory to store downloaded data.
- split:
Optional specification of which split to load.
- data_files:
Optional specification of particular data files to load.
- revision:
Optional. The revision of the dataset. Often the commit id. Use in case you want to set the dataset version.
- streaming (bool):
indicating if streaming should be used.
- filtering_lambda (str, optional):
A lambda function for filtering the data after loading.
- num_proc (int, optional):
Specifies the number of processes to use for parallel dataset loading.
- Example:
Loading glue’s mrpc dataset
load_hf = LoadHF(path='glue', name='mrpc')
Explanation about Set¶
Sets specified fields in each instance, in a given stream or all streams (default), with specified values. If fields exist, updates them, if do not exist – adds them.
- Args:
fields (Dict[str, object]): The fields to add to each instance. Use ‘/’ to access inner fields
use_deepcopy (bool) : Deep copy the input value to avoid later modifications
- Examples:
# Set a value of a list consisting of “positive” and “negative” do field “classes” to each and every instance of all streams
Set(fields={"classes": ["positive","negatives"]})# In each and every instance of all streams, field “span” is to become a dictionary containing a field “start”, in which the value 0 is to be set
Set(fields={"span/start": 0}# In all instances of stream “train” only, Set field “classes” to have the value of a list consisting of “positive” and “negative”
Set(fields={"classes": ["positive","negatives"], apply_to_stream=["train"]})# Set field “classes” to have the value of a given list, preventing modification of original list from changing the instance.
Set(fields={"classes": alist}), use_deepcopy=True)if now alist is modified, still the instances remain intact.
Explanation about MapInstanceValues¶
A class used to map instance values into other values.
This class is a type of
InstanceOperator, it maps values of instances in a stream using predefined mappers.
- Args:
- mappers (Dict[str, Dict[str, Any]]):
The mappers to use for mapping instance values. Keys are the names of the fields to undergo mapping, and values are dictionaries that define the mapping from old values to new values. Note that mapped values are defined by their string representation, so mapped values are converted to strings before being looked up in the mappers.
- strict (bool):
If True, the mapping is applied strictly. That means if a value does not exist in the mapper, it will raise a KeyError. If False, values that are not present in the mapper are kept as they are.
- process_every_value (bool):
If True, all fields to be mapped should be lists, and the mapping is to be applied to their individual elements. If False, mapping is only applied to a field containing a single value.
- Examples:
MapInstanceValues(mappers={"a": {"1": "hi", "2": "bye"}})replaces"1"with"hi"and"2"with"bye"in field"a"in all instances of all streams: instance{"a": 1, "b": 2}becomes{"a": "hi", "b": 2}. Note that the value of"b"remained intact, since field-name"b"does not participate in the mappers, and that1was casted to"1"before looked up in the mapper of"a".
MapInstanceValues(mappers={"a": {"1": "hi", "2": "bye"}}, process_every_value=True): Assuming field"a"is a list of values, potentially including"1"-s and"2"-s, this replaces each such"1"with"hi"and"2"– with"bye"in all instances of all streams: instance{"a": ["1", "2"], "b": 2}becomes{"a": ["hi", "bye"], "b": 2}.
MapInstanceValues(mappers={"a": {"1": "hi", "2": "bye"}}, strict=True): To ensure that all values of field"a"are mapped in every instance, usestrict=True. Input instance{"a":"3", "b": 2}will raise an exception per the above call, because"3"is not a key in the mapper of"a".
MapInstanceValues(mappers={"a": {str([1,2,3,4]): "All", str([]): "None"}}, strict=True)replaces a list[1,2,3,4]with the string"All"and an empty list by string"None".
References: templates.classification.multi_class.all, tasks.classification.multi_class
Read more about catalog usage here.