The dataset preview is not available for this split.
Error code: StreamingRowsError Exception: FileNotFoundError Message: https://ixa2.si.ehu.es/convai/doqa-v2.1.zip Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/aiohttp/connector.py", line 980, in _wrap_create_connection return await self._loop.create_connection(*args, **kwargs) # type: ignore[return-value] # noqa File "/usr/local/lib/python3.9/asyncio/base_events.py", line 1090, in create_connection transport, protocol = await self._create_connection_transport( File "/usr/local/lib/python3.9/asyncio/base_events.py", line 1120, in _create_connection_transport await waiter File "/usr/local/lib/python3.9/asyncio/sslproto.py", line 534, in data_received ssldata, appdata = self._sslpipe.feed_ssldata(data) File "/usr/local/lib/python3.9/asyncio/sslproto.py", line 188, in feed_ssldata self._sslobj.do_handshake() File "/usr/local/lib/python3.9/ssl.py", line 945, in do_handshake self._sslobj.do_handshake() ssl.SSLCertVerificationError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: unable to get local issuer certificate (_ssl.c:1129) The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/http.py", line 417, in _info await _file_info( File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/http.py", line 833, in _file_info r = await session.get(url, allow_redirects=ar, **kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/aiohttp/client.py", line 536, in _request conn = await self._connector.connect( File "/src/services/worker/.venv/lib/python3.9/site-packages/aiohttp/connector.py", line 540, in connect proto = await self._create_connection(req, traces, timeout) File "/src/services/worker/.venv/lib/python3.9/site-packages/aiohttp/connector.py", line 901, in _create_connection _, proto = await self._create_direct_connection(req, traces, timeout) File "/src/services/worker/.venv/lib/python3.9/site-packages/aiohttp/connector.py", line 1206, in _create_direct_connection raise last_exc File "/src/services/worker/.venv/lib/python3.9/site-packages/aiohttp/connector.py", line 1175, in _create_direct_connection transp, proto = await self._wrap_create_connection( File "/src/services/worker/.venv/lib/python3.9/site-packages/aiohttp/connector.py", line 982, in _wrap_create_connection raise ClientConnectorCertificateError(req.connection_key, exc) from exc aiohttp.client_exceptions.ClientConnectorCertificateError: Cannot connect to host ixa2.si.ehu.es:443 ssl:True [SSLCertVerificationError: (1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: unable to get local issuer certificate (_ssl.c:1129)')] The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/first_rows.py", line 571, in compute_first_rows_response rows = get_rows( File "/src/services/worker/src/worker/job_runners/first_rows.py", line 162, in decorator return func(*args, **kwargs) File "/src/services/worker/src/worker/job_runners/first_rows.py", line 218, in get_rows rows_plus_one = list(itertools.islice(ds, rows_max_number + 1)) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 937, in __iter__ for key, example in ex_iterable: File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 113, in __iter__ yield from self.generate_examples_fn(**self.kwargs) File "/tmp/modules-cache/datasets_modules/datasets/doqa/5bc0cb24c4eeb61f2004f1e0ba9b4135cd5a814770b0a042dbf0725e1d2ad1eb/doqa.py", line 158, in _generate_examples with open(filepath, encoding="utf-8") as f: File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/streaming.py", line 70, in wrapper return function(*args, use_auth_token=use_auth_token, **kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 495, in xopen file_obj = fsspec.open(file, mode=mode, *args, **kwargs).open() File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 419, in open return open_files( File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 272, in open_files fs, fs_token, paths = get_fs_token_paths( File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 586, in get_fs_token_paths fs = filesystem(protocol, **inkwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/registry.py", line 253, in filesystem return cls(**storage_options) File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 76, in __call__ obj = super().__call__(*args, **kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/zip.py", line 58, in __init__ self.fo = fo.__enter__() # the whole instance is a context File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 102, in __enter__ f = self.fs.open(self.path, mode=mode) File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 1151, in open f = self._open( File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/http.py", line 356, in _open size = size or self.info(path, **kwargs)["size"] File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/asyn.py", line 115, in wrapper return sync(self.loop, func, *args, **kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/asyn.py", line 100, in sync raise return_result File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/asyn.py", line 55, in _runner result[0] = await coro File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/http.py", line 430, in _info raise FileNotFoundError(url) from exc FileNotFoundError: https://ixa2.si.ehu.es/convai/doqa-v2.1.zip
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Dataset Card for "doqa"
Dataset Summary
DoQA is a dataset for accessing Domain Specific FAQs via conversational QA that contains 2,437 information-seeking question/answer dialogues (10,917 questions in total) on three different domains: cooking, travel and movies. Note that we include in the generic concept of FAQs also Community Question Answering sites, as well as corporate information in intranets which is maintained in textual form similar to FAQs, often referred to as internal “knowledge bases”.
These dialogues are created by crowd workers that play the following two roles: the user who asks questions about a given topic posted in Stack Exchange (https://stackexchange.com/), and the domain expert who replies to the questions by selecting a short span of text from the long textual reply in the original post. The expert can rephrase the selected span, in order to make it look more natural. The dataset covers unanswerable questions and some relevant dialogue acts.
DoQA enables the development and evaluation of conversational QA systems that help users access the knowledge buried in domain specific FAQs.
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
cooking
- Size of downloaded dataset files: 4.00 MB
- Size of the generated dataset: 10.79 MB
- Total amount of disk used: 14.79 MB
An example of 'train' looks as follows.
This example was too long and was cropped:
{
"answers": {
"answer_start": [852],
"text": ["CANNOTANSWER"]
},
"background": "\"So, over mixing batter forms gluten, which in turn hardens the cake. Fine.The problem is that I don't want lumps in the cakes, ...",
"context": "\"Milk won't help you - it's mostly water, and gluten develops from flour (more accurately, specific proteins in flour) and water...",
"followup": "n",
"id": "C_64ce44d5f14347f488eb04b50387f022_q#2",
"orig_answer": {
"answer_start": [852],
"text": ["CANNOTANSWER"]
},
"question": "Ok. What can I add to make it more softer and avoid hardening?",
"title": "What to add to the batter of the cake to avoid hardening when the gluten formation can't be avoided?",
"yesno": "x"
}
movies
- Size of downloaded dataset files: 4.00 MB
- Size of the generated dataset: 3.02 MB
- Total amount of disk used: 7.02 MB
An example of 'test' looks as follows.
This example was too long and was cropped:
{
"answers": {
"answer_start": [852],
"text": ["CANNOTANSWER"]
},
"background": "\"So, over mixing batter forms gluten, which in turn hardens the cake. Fine.The problem is that I don't want lumps in the cakes, ...",
"context": "\"Milk won't help you - it's mostly water, and gluten develops from flour (more accurately, specific proteins in flour) and water...",
"followup": "n",
"id": "C_64ce44d5f14347f488eb04b50387f022_q#2",
"orig_answer": {
"answer_start": [852],
"text": ["CANNOTANSWER"]
},
"question": "Ok. What can I add to make it more softer and avoid hardening?",
"title": "What to add to the batter of the cake to avoid hardening when the gluten formation can't be avoided?",
"yesno": "x"
}
travel
- Size of downloaded dataset files: 4.00 MB
- Size of the generated dataset: 3.07 MB
- Total amount of disk used: 7.07 MB
An example of 'test' looks as follows.
This example was too long and was cropped:
{
"answers": {
"answer_start": [852],
"text": ["CANNOTANSWER"]
},
"background": "\"So, over mixing batter forms gluten, which in turn hardens the cake. Fine.The problem is that I don't want lumps in the cakes, ...",
"context": "\"Milk won't help you - it's mostly water, and gluten develops from flour (more accurately, specific proteins in flour) and water...",
"followup": "n",
"id": "C_64ce44d5f14347f488eb04b50387f022_q#2",
"orig_answer": {
"answer_start": [852],
"text": ["CANNOTANSWER"]
},
"question": "Ok. What can I add to make it more softer and avoid hardening?",
"title": "What to add to the batter of the cake to avoid hardening when the gluten formation can't be avoided?",
"yesno": "x"
}
Data Fields
The data fields are the same among all splits.
cooking
title
: astring
feature.background
: astring
feature.context
: astring
feature.question
: astring
feature.id
: astring
feature.answers
: a dictionary feature containing:text
: astring
feature.answer_start
: aint32
feature.
followup
: astring
feature.yesno
: astring
feature.orig_answer
: a dictionary feature containing:text
: astring
feature.answer_start
: aint32
feature.
movies
title
: astring
feature.background
: astring
feature.context
: astring
feature.question
: astring
feature.id
: astring
feature.answers
: a dictionary feature containing:text
: astring
feature.answer_start
: aint32
feature.
followup
: astring
feature.yesno
: astring
feature.orig_answer
: a dictionary feature containing:text
: astring
feature.answer_start
: aint32
feature.
travel
title
: astring
feature.background
: astring
feature.context
: astring
feature.question
: astring
feature.id
: astring
feature.answers
: a dictionary feature containing:text
: astring
feature.answer_start
: aint32
feature.
followup
: astring
feature.yesno
: astring
feature.orig_answer
: a dictionary feature containing:text
: astring
feature.answer_start
: aint32
feature.
Data Splits
cooking
train | validation | test | |
---|---|---|---|
cooking | 4612 | 911 | 1797 |
movies
test | |
---|---|
movies | 1884 |
travel
test | |
---|---|
travel | 1713 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
Citation Information
@misc{campos2020doqa,
title={DoQA -- Accessing Domain-Specific FAQs via Conversational QA},
author={Jon Ander Campos and Arantxa Otegi and Aitor Soroa and Jan Deriu and Mark Cieliebak and Eneko Agirre},
year={2020},
eprint={2005.01328},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Contributions
Thanks to @mariamabarham, @thomwolf, @lhoestq for adding this dataset.
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