Distantly Labeling Data for Large Scale Cross-Document Coreference

Cross-document coreference, the problem of resolving entity mentions across multi-document collections, is crucial to automated knowledge base construction and data mining tasks. However, the scarcity of large labeled data sets has hindered supervised machine learning research for this task. In this paper we develop and demonstrate an approach based on ``distantly-labeling'' a data set from which we can train a discriminative cross-document coreference model. In particular we build a dataset of more than a million people mentions extracted from 3.5 years of New York Times articles, leverage Wikipedia for distant labeling with a generative model (and measure the reliability of such labeling); then we train and evaluate a conditional random field coreference model that has factors on cross-document entities as well as mention-pairs. This coreference model obtains high accuracy in resolving mentions and entities that are not present in the training data, indicating applicability to non-Wikipedia data. Given the large amount of data, our work is also an exercise demonstrating the scalability of our approach.Comment: 16 pages, submitted to ECML 201

Retrieving with good sense

Although always present in text, word sense ambiguity only recently became regarded as a problem to information retrieval which was potentially solvable. The growth of interest in word senses resulted from new directions taken in disambiguation research. This paper first outlines this research and surveys the resulting efforts in information retrieval. Although the majority of attempts to improve retrieval effectiveness were unsuccessful, much was learnt from the research. Most notably a notion of under what circumstance disambiguation may prove of use to retrieval

Affines, Ambiguity, and Meaning in Hokkien Kin Terms

This is a publisher's version of an article published in the journal Ethnology in 1981. The offprint is posted here in accordance with existing publisher policy, or by special permission via correspondence.tru

Beyond the Win: Pathways for Policy Implementation

When it comes to policy, a lot of attention is given to "the win." Whether it is something new and big like the Affordable Care Act, a piece of legislation in a large federal omnibus bill, or inclusion of critical language in a state policy, seeing the fruits of advocacy efforts put into law makes advocates and champions feel that their hard work, often many years in the making, has paid off.However, in reality, "the win" is just the beginning -- a necessary first step in a much longer and equally as fraught process of policy implementation. Once a policy is created, there are numerous factors that shape and determine how that policy is implemented -- and ultimately, the impact it will have -- regardless of how well the policy is formulated. Some of these factors include rulemaking, funding, capacity of local implementing agencies, and fights to repeal or modify wins, among many others.And, just as in the case of "the win," advocacy plays an important role in shaping implementation whether in advocating across these factors or participating in ongoing monitoring over time. Interestingly, while the role of advocacy in agenda setting, policy formulation, and policy adoption has been widely explored in theory and practice, the role of advocacy in the policy implementation process has received less attention in the literature.To learn more about the role of advocacy at the policy implementation stage, ORS Impact spoke with organizations that engage in, or provide funding for, advocacy efforts at the state and/or federal level. We focused on the following questions:When had advocates played a positive role in policy implementation?When had implementation not gone as well as expected, and what did advocates take away from that?Our conversations yielded important learnings about the unique characteristics of, and range of approaches to, advocacy efforts during the implementation phase. The two following scenarios illustrate some of the different types and levels of advocacy intervention, as well as the results they produce, to demonstrate the ways advocacy can play out when shifting from policymaking to implementation

Effective performance management of inter-organisational collaborations through the construction of multiple identities

Although inter-organisational collaborations can offer better services, their performance management is complex and can often fail. Through the exploration of multiple (collaborative and non-collaborative) identities formed by partners, the paper offers guidelines for a more effective performance management of inter-organisational collaborations. More specifically, drawing upon a longitudinal qualitative study of a Greek inter-organisational collaboration, the findings of the research illustrate that both collaborative and non-collaborative identities can lead to better collaboration performance. Secondly, the study suggests that it is better to maintain the tension between stability and change within the collaborative process than resolve it. Finally, it offers four collaborative patterns for a more effective performance management of inter-organisational collaborations

Sloppy Identity

Although sloppy interpretation is usually accounted for by theories of ellipsis, it often arises in non-elliptical contexts. In this paper, a theory of sloppy interpretation is provided which captures this fact. The underlying idea is that sloppy interpretation results from a semantic constraint on parallel structures and the theory is shown to predict sloppy readings for deaccented and paycheck sentences as well as relational-, event-, and one-anaphora. It is further shown to capture the interaction of sloppy/strict ambiguity with quantification and binding.Comment: 20 page