CMLC-5 + BigNLP / 5th Workshop on Challenges in the Management of Large Corpora and Big Data and Natural Language Processing
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This article describes a series of ongoing efforts at the Stanford Literary Lab to manage a large collection of literary corpora (~40 billion words). This work is marked by a tension between two competing requirements – the corpora need to be merged together into higher-order collections that can be analyzed as units; but, at the same time, it’s also necessary to preserve granular access to the original metadata and relational organization of each individual corpus. We describe a set of data management practices that try to accommodate both of these requirements – Apache Spark is used to index data as Parquet tables on an HPC cluster at Stanford. Crucially, the approach distinguishes between what we call “canonical” and “combined” corpora, a variation on the well-established notion of a “virtual corpus” (Kupietz et al., 2014; Jakubíek et al., 2014; van Uytvanck, 2010).
This paper outlines the broad research context and rationale for a new international comparable corpus (ICC). The ICC is to be largely modelled on the text categories and their quantities the International Corpus of English with only a few changes. The corpus will initially begin with nine European languages but others may join in due course. The paper reports on those and other agreements made at the inaugural planning meeting in Prague on 22-23 June 2017. It also sets out the project’s goals for its first two years.