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Open Mind Common Sense is a knowledge acquisition system designed to acquire commonsense knowledge from the general public over the web. We describe and evaluate our first fielded system, which enabled the construction of a 400,000 assertion commonsense knowledge base. We then discuss how our second-generation system addresses weaknesses discovered in the(More)
Entity linking systems link noun-phrase mentions in text to their corresponding Wikipedia articles. However, NLP applications would gain from the ability to detect and type all entities mentioned in text, including the long tail of entities not prominent enough to have their own Wikipedia articles. In this paper we show that once the Wikipedia entities(More)
This paper investigates entity linking over millions of high-precision extractions from a corpus of 500 million Web documents, toward the goal of creating a useful knowledge base of general facts. This paper is the first to report on entity linking over this many extractions, and describes new opportunities (such as corpus-level features) and challenges we(More)
We predict entity type distributions in Web search queries via probabilistic inference in graphical models that capture how entitybearing queries are generated. We jointly model the interplay between latent user intents that govern queries and unobserved entity types, leveraging observed signals from query formulations and document clicks. We apply the(More)
We introduce an entity-centric search experience, called Active Objects, in which entity-bearing queries are paired with actions that can be performed on the entities. For example, given a query for a specific flashlight, we aim to present actions such as reading reviews, watching demo videos, and finding the best price online. In an annotation study(More)
Determining whether a textual phrase denotes a functional relation (i.e., a relation that maps each domain element to a unique range element) is useful for numerous NLP tasks such as synonym resolution and contradiction detection. Previous work on this problem has relied on either counting methods or lexico-syntactic patterns. However, determining whether a(More)
We examine the relationship between quality-based manufacturing strategy and the use of different types of performance measures, as well as their separate and joint effects on performance. A key part of our investigation is the distinction between financial and both objective and subjective nonfinancial measures. Our results support the view that(More)
Machine reading is a long-standing goal of AI and NLP. In recent years, tremendous progress has been made in developing machine learning approaches for many of its subtasks such as parsing, information extraction, and question answering. However, existing end-to-end solutions typically require substantial amount of human efforts (e.g., labeled data and/or(More)
After 1 July 2006, a major challenge that the manufacturing industry has to confront now is the effect of the lead-free equipment system selection process on companies’ capital expenditure decision. With capital investment, the criteria may be financial (e.g. expected cash flows) and non-financial (e.g. product quality). We use a systems approach with the(More)