@inproceedings{strassel-etal-2010-darpa,
title = "The {DARPA} Machine Reading Program - Encouraging Linguistic and Reasoning Research with a Series of Reading Tasks",
author = "Strassel, Stephanie and
Adams, Dan and
Goldberg, Henry and
Herr, Jonathan and
Keesing, Ron and
Oblinger, Daniel and
Simpson, Heather and
Schrag, Robert and
Wright, Jonathan",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Rosner, Mike and
Tapias, Daniel",
booktitle = "Proceedings of the Seventh International Conference on Language Resources and Evaluation ({LREC}'10)",
month = may,
year = "2010",
address = "Valletta, Malta",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/L10-1595/",
abstract = "The goal of DARPAs Machine Reading (MR) program is nothing less than making the worlds natural language corpora available for formal processing. Most text processing research has focused on locating mission-relevant text (information retrieval) and on techniques for enriching text by transforming it to other forms of text (translation, summarization) {\textemdash} always for use by humans. In contrast, MR will make knowledge contained in text available in forms that machines can use for automated processing. This will be done with little human intervention. Machines will learn to read from a few examples and they will read to learn what they need in order to answer questions or perform some reasoning task. Three independent Reading Teams are building universal text engines which will capture knowledge from naturally occurring text and transform it into the formal representations used by Artificial Intelligence. An Evaluation Team is selecting and annotating text corpora with task domain concepts, creating model reasoning systems with which the reading systems will interact, and establishing question-answer sets and evaluation protocols to measure progress toward this goal. We describe development of the MR evaluation framework, including test protocols, linguistic resources and technical infrastructure."
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<abstract>The goal of DARPAs Machine Reading (MR) program is nothing less than making the worlds natural language corpora available for formal processing. Most text processing research has focused on locating mission-relevant text (information retrieval) and on techniques for enriching text by transforming it to other forms of text (translation, summarization) — always for use by humans. In contrast, MR will make knowledge contained in text available in forms that machines can use for automated processing. This will be done with little human intervention. Machines will learn to read from a few examples and they will read to learn what they need in order to answer questions or perform some reasoning task. Three independent Reading Teams are building universal text engines which will capture knowledge from naturally occurring text and transform it into the formal representations used by Artificial Intelligence. An Evaluation Team is selecting and annotating text corpora with task domain concepts, creating model reasoning systems with which the reading systems will interact, and establishing question-answer sets and evaluation protocols to measure progress toward this goal. We describe development of the MR evaluation framework, including test protocols, linguistic resources and technical infrastructure.</abstract>
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%0 Conference Proceedings
%T The DARPA Machine Reading Program - Encouraging Linguistic and Reasoning Research with a Series of Reading Tasks
%A Strassel, Stephanie
%A Adams, Dan
%A Goldberg, Henry
%A Herr, Jonathan
%A Keesing, Ron
%A Oblinger, Daniel
%A Simpson, Heather
%A Schrag, Robert
%A Wright, Jonathan
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Rosner, Mike
%Y Tapias, Daniel
%S Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10)
%D 2010
%8 May
%I European Language Resources Association (ELRA)
%C Valletta, Malta
%F strassel-etal-2010-darpa
%X The goal of DARPAs Machine Reading (MR) program is nothing less than making the worlds natural language corpora available for formal processing. Most text processing research has focused on locating mission-relevant text (information retrieval) and on techniques for enriching text by transforming it to other forms of text (translation, summarization) — always for use by humans. In contrast, MR will make knowledge contained in text available in forms that machines can use for automated processing. This will be done with little human intervention. Machines will learn to read from a few examples and they will read to learn what they need in order to answer questions or perform some reasoning task. Three independent Reading Teams are building universal text engines which will capture knowledge from naturally occurring text and transform it into the formal representations used by Artificial Intelligence. An Evaluation Team is selecting and annotating text corpora with task domain concepts, creating model reasoning systems with which the reading systems will interact, and establishing question-answer sets and evaluation protocols to measure progress toward this goal. We describe development of the MR evaluation framework, including test protocols, linguistic resources and technical infrastructure.
%U https://aclanthology.org/L10-1595/
Markdown (Informal)
[The DARPA Machine Reading Program - Encouraging Linguistic and Reasoning Research with a Series of Reading Tasks](https://aclanthology.org/L10-1595/) (Strassel et al., LREC 2010)
ACL
- Stephanie Strassel, Dan Adams, Henry Goldberg, Jonathan Herr, Ron Keesing, Daniel Oblinger, Heather Simpson, Robert Schrag, and Jonathan Wright. 2010. The DARPA Machine Reading Program - Encouraging Linguistic and Reasoning Research with a Series of Reading Tasks. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), Valletta, Malta. European Language Resources Association (ELRA).