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Wall St. Bears Claw Back Into the Black (Reuters) Reuters - Short-sellers, Wall Street's dwindling\band of ultra-cynics, are seeing green again.
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Carlyle Looks Toward Commercial Aerospace (Reuters) Reuters - Private investment firm Carlyle Group,\which has a reputation for making well-timed and occasionally\controversial plays in the defense industry, has quietly placed\its bets on another part of the market.
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Oil and Economy Cloud Stocks' Outlook (Reuters) Reuters - Soaring crude prices plus worries\about the economy and the outlook for earnings are expected to\hang over the stock market next week during the depth of the\summer doldrums.
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record-2
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Iraq Halts Oil Exports from Main Southern Pipeline (Reuters) Reuters - Authorities have halted oil export\flows from the main pipeline in southern Iraq after\intelligence showed a rebel militia could strike\infrastructure, an oil official said on Saturday.
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Oil prices soar to all-time record, posing new menace to US economy (AFP) AFP - Tearaway world oil prices, toppling records and straining wallets, present a new economic menace barely three months before the US presidential elections.
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Stocks End Up, But Near Year Lows (Reuters) Reuters - Stocks ended slightly higher on Friday\but stayed near lows for the year as oil prices surged past #36;46\a barrel, offsetting a positive outlook from computer maker\Dell Inc. (DELL.O)
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Money Funds Fell in Latest Week (AP) AP - Assets of the nation's retail money market mutual funds fell by #36;1.17 billion in the latest week to #36;849.98 trillion, the Investment Company Institute said Thursday.
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Fed minutes show dissent over inflation (USATODAY.com) USATODAY.com - Retail sales bounced back a bit in July, and new claims for jobless benefits fell last week, the government said Thursday, indicating the economy is improving from a midsummer slump.
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record-7
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Safety Net (Forbes.com) Forbes.com - After earning a PH.D. in Sociology, Danny Bazil Riley started to work as the general manager at a commercial real estate firm at an annual base salary of #36;70,000. Soon after, a financial planner stopped by his desk to drop off brochures about insurance benefits available through his employer. But, at 32, "buying insurance was the furthest thing from my mind," says Riley.
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record-8
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Wall St. Bears Claw Back Into the Black NEW YORK (Reuters) - Short-sellers, Wall Street's dwindling band of ultra-cynics, are seeing green again.
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record-9
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Oil and Economy Cloud Stocks' Outlook NEW YORK (Reuters) - Soaring crude prices plus worries about the economy and the outlook for earnings are expected to hang over the stock market next week during the depth of the summer doldrums.
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record-10
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No Need for OPEC to Pump More-Iran Gov TEHRAN (Reuters) - OPEC can do nothing to douse scorching oil prices when markets are already oversupplied by 2.8 million barrels per day (bpd) of crude, Iran's OPEC governor said Saturday, warning that prices could fall sharply.
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record-11
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Non-OPEC Nations Should Up Output-Purnomo JAKARTA (Reuters) - Non-OPEC oil exporters should consider increasing output to cool record crude prices, OPEC President Purnomo Yusgiantoro said on Sunday.
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record-12
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Google IPO Auction Off to Rocky Start WASHINGTON/NEW YORK (Reuters) - The auction for Google Inc.'s highly anticipated initial public offering got off to a rocky start on Friday after the Web search company sidestepped a bullet from U.S. securities regulators.
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Dollar Falls Broadly on Record Trade Gap NEW YORK (Reuters) - The dollar tumbled broadly on Friday after data showing a record U.S. trade deficit in June cast fresh doubts on the economy's recovery and its ability to draw foreign capital to fund the growing gap.
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record-14
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Rescuing an Old Saver If you think you may need to help your elderly relatives with their finances, don't be shy about having the money talk -- soon.
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record-15
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Kids Rule for Back-to-School The purchasing power of kids is a big part of why the back-to-school season has become such a huge marketing phenomenon.
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record-16
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In a Down Market, Head Toward Value Funds There is little cause for celebration in the stock market these days, but investors in value-focused mutual funds have reason to feel a bit smug -- if only because they've lost less than the folks who stuck with growth.
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record-17
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US trade deficit swells in June The US trade deficit has exploded 19 to a record \$55.8bn as oil costs drove imports higher, according to a latest figures.
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record-18
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Shell 'could be target for Total' Oil giant Shell could be bracing itself for a takeover attempt, possibly from French rival Total, a press report claims.
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record-19
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Google IPO faces Playboy slip-up The bidding gets underway for Google's public offering, despite last-minute worries over an interview with its bosses in Playboy magazine.
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record-20
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Eurozone economy keeps growing Official figures show the 12-nation eurozone economy continues to grow, but there are warnings it may slow down later in the year.
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record-21
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Expansion slows in Japan Economic growth in Japan slows down as the country experiences a drop in domestic and corporate spending.
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record-22
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Rand falls on shock SA rate cut Interest rates are trimmed to 7.5 by the South African central bank, but the lack of warning hits the rand and surprises markets.
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record-23
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Dataset Card for end2end_textclassification_with_vectors

This dataset has been created with Argilla.

As shown in the sections below, this dataset can be loaded into Argilla as explained in Load with Argilla, or used directly with the datasets library in Load with datasets.

Dataset Summary

This dataset contains:

  • A dataset configuration file conforming to the Argilla dataset format named argilla.yaml. This configuration file will be used to configure the dataset when using the FeedbackDataset.from_huggingface method in Argilla.

  • Dataset records in a format compatible with HuggingFace datasets. These records will be loaded automatically when using FeedbackDataset.from_huggingface and can be loaded independently using the datasets library via load_dataset.

  • The annotation guidelines that have been used for building and curating the dataset, if they've been defined in Argilla.

Load with Argilla

To load with Argilla, you'll just need to install Argilla as pip install argilla --upgrade and then use the following code:

import argilla as rg

ds = rg.FeedbackDataset.from_huggingface("argilla/end2end_textclassification_with_vectors")

Load with datasets

To load this dataset with datasets, you'll just need to install datasets as pip install datasets --upgrade and then use the following code:

from datasets import load_dataset

ds = load_dataset("argilla/end2end_textclassification_with_vectors")

Supported Tasks and Leaderboards

This dataset can contain multiple fields, questions and responses so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the Dataset Structure section.

There are no leaderboards associated with this dataset.

Languages

[More Information Needed]

Dataset Structure

Data in Argilla

The dataset is created in Argilla with: fields, questions, suggestions, metadata, vectors, and guidelines.

The fields are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.

Field Name Title Type Required Markdown
text Text FieldTypes.text True False

The questions are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label_selection, multi_label_selection, or ranking.

Question Name Title Type Required Description Values/Labels
label Label QuestionTypes.label_selection True Classify the text by selecting the correct label from the given list of labels. ['World', 'Sports', 'Business', 'Sci/Tech']

The suggestions are human or machine generated recommendations for each question to assist the annotator during the annotation process, so those are always linked to the existing questions, and named appending "-suggestion" and "-suggestion-metadata" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above, but the column name is appended with "-suggestion" and the metadata is appended with "-suggestion-metadata".

The metadata is a dictionary that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the metadata_properties defined in the dataset configuration file in argilla.yaml.

✨ NEW The vectors are different columns that contain a vector in floating point, which is constraint to the pre-defined dimensions in the vectors_settings when configuring the vectors within the dataset itself, also the dimensions will always be 1-dimensional. The vectors are optional and identified by the pre-defined vector name in the dataset configuration file in argilla.yaml.

Vector Name Title Dimensions
sentence_embedding Sentence Embedding [1, 384]
Metadata Name Title Type Values Visible for Annotators

The guidelines, are optional as well, and are just a plain string that can be used to provide instructions to the annotators. Find those in the annotation guidelines section.

Data Instances

An example of a dataset instance in Argilla looks as follows:

{
    "external_id": "record-0",
    "fields": {
        "text": "Wall St. Bears Claw Back Into the Black (Reuters) Reuters - Short-sellers, Wall Street\u0027s dwindling\\band of ultra-cynics, are seeing green again."
    },
    "metadata": {},
    "responses": [],
    "suggestions": [],
    "vectors": {
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    }
}

While the same record in HuggingFace datasets looks as follows:

{
    "external_id": "record-0",
    "label": [],
    "label-suggestion": null,
    "label-suggestion-metadata": {
        "agent": null,
        "score": null,
        "type": null
    },
    "metadata": "{}",
    "text": "Wall St. Bears Claw Back Into the Black (Reuters) Reuters - Short-sellers, Wall Street\u0027s dwindling\\band of ultra-cynics, are seeing green again.",
    "vectors": {
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    }
}

Data Fields

Among the dataset fields, we differentiate between the following:

  • Fields: These are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.

    • text is of type FieldTypes.text.
  • Questions: These are the questions that will be asked to the annotators. They can be of different types, such as RatingQuestion, TextQuestion, LabelQuestion, MultiLabelQuestion, and RankingQuestion.

    • label is of type QuestionTypes.label_selection with the following allowed values ['World', 'Sports', 'Business', 'Sci/Tech'], and description "Classify the text by selecting the correct label from the given list of labels.".
  • Suggestions: As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable.

    • (optional) label-suggestion is of type QuestionTypes.label_selection with the following allowed values ['World', 'Sports', 'Business', 'Sci/Tech'].
  • ✨ NEW Vectors: As of Argilla 1.19.0, the vectors have been included in order to add support for similarity search to explore similar records based on vector search powered by the search engine defined. The vectors are optional and cannot be seen within the UI, those are uploaded and internally used. Also the vectors will always be optional, and only the dimensions previously defined in their settings.

    • (optional) sentence_embedding is of type float32 and has a dimension of (1, 384).

Additionally, we also have two more fields that are optional and are the following:

  • metadata: This is an optional field that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the metadata_properties defined in the dataset configuration file in argilla.yaml.
  • external_id: This is an optional field that can be used to provide an external ID for the dataset record. This can be useful if you want to link the dataset record to an external resource, such as a database or a file.

Data Splits

The dataset contains a single split, which is train.

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation guidelines

Classify the articles into one of the four categories.

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

[More Information Needed]

Contributions

[More Information Needed]

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