18 Yahoo Answers fails that will leave you scratching your head
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The queries are tagged by linguists for syntactic segmentation and dependency parse tree within each segment. A major challenge is to be able to accurately detect entities, in new languages, at scale, with limited labeled data available, and while consuming a limited amount of resources memory and processing power.
In this dataset we release datapacks for English, Spanish, and Chinese built for our unsupervised, accurate, and extensible multilingual named entity recognition and linking system Fast Entity Linker. In our system, we use entity embeddings, click-log data, and efficient clustering methods to achieve high precision.
The system achieves a low memory footprint and fast execution times by using compressed data-structures and aggressive hashing functions. The models released in this dataset include "entity embeddings" and "wikipedia click-log data". Entity Embeddings are vector-based representations that capture how entities are referred to in language contexts. We train entity embeddings using Wikipedia articles and use hyperlinks in the articles to their canonical forms for their associated entities.
Wikipedia click-logs gives very useful signals to disambiguate partial or ambiguous entity mentions, such as Obama Michelle or BarackLiverpool City or Football teamor Fox Person or Organization. We extract the in-wiki links from Wikipedia and create pairs alias, entity where the alias is the text in the anchor and the entity is the id of a Wikipedia page pointed out by an outgoing link. Dataset has been added to your cart View Cart L31 - Questions on Yahoo Answers labeled as either informational or conversational, version 1.
Each question include a URL to its Yahoo Answers page, its title, description, high-level category one of 26direct category, and a label marking it as informational '0' or conversational '1'. A small subset of the questions is marked as borderline '2'. We annotated the dataset at the comment-level and the thread-level. The annotations include 6 dimensions of individual comments and 3 dimensions of threads on the whole.
The coding was done by professional, trained editors and untrained crowdsourced workers. The corpus contains annotations for a novel corpus of 2. Multilabel learning is at the core of this problem and recently got a revived interest.
There are many standard datasets available for this task but all of them provide features and not the actual text of the documents. This corpus provides the actual text so that the researchers can derive their own features that are good best for their algorithms.
Yahoo! Answers - Wikipedia
Official[ edit ] This type of badge is found on the name of celebrities like mentioned above and government departments like the health department. Studies of user typology on the site have revealed that some users answer from personal knowledge — "specialists" — while others use external sources to construct answers — "synthesists", with synthesists tending to accumulate more reward points.
They also show that answer length is a good predictor of "best answer" choice.
Answers is not very deep. Answers' reputation of being a source of entertainment rather than a fact based question and answer platform,   and for the reliability, validity, and relevance of its answers.
A study found that Yahoo! Answers is suboptimal for questions requiring factual answers and that the quality decreases as the number of users increases. Answers provides, particularly the persistence of inaccuracies, the inability to correct them, and a point structure that rewards participation more readily than accuracy, all indicate that the site is oriented towards encouraging use of the site, not offering accurate answers to questions.
Answers itself indicate that Yahoo! Answers attracts a large number of trolls. The site does not have a system that filters the correct answers from the incorrect answers.
Answers, once the "best answer" was chosen, there was no way to add more answers nor to improve or challenge the best answer chosen by the question asker; there is a display of thumbs down or thumbs up for each answer, but viewers cannot vote. In Aprilthis was changed to allow for additional answers after a best answer is chosen, but the best answer can never be changed.