We borrowed this idea from the field of translation studies, where translation equivalents are aligned and then stored as translation memory to be used during later translation tasks. What interested us was the idea of aligning linguistic data across languages and retrieving aligned segments for the purposes of analysis and comparison.
One of the remarkable features of Kiranti languages in Eastern Nepal is that their mythology is surprisingly similar: in some cases, perfect calques of sentences are found across different language versions of a same story. This seemed like a good starting point for building a corpus of aligned material based on resolutely native data, as opposed to more artificial (but still interesting) material such as Frog stories and Pear Stories.
We have set up a prototype for the aligntment of stories, and so far, it is quite promising: we have aligned three different versions of the story of Kakcilip–in Thulung, Koyi and Khaling–in such a way that similar content across languages is tagged with a Similarity label.
The Similarity labels appear above the sentence numbers in the full-text versions of the story in the different languages. When a sentence with such a label is selected, it leads to a view of that same sentence in the languages involved in the similarity.
We had, of course, to define the notion of similarity for the purposes of this alignment: for the time being, our working definition is that it concerns a segment of text of similar narrative function or content. This allows us to align, in addition to material sharing lexical and morphosyntactic features, sentences in different versions that outwardly have no connection (different names of protagonists, different actions, different objects involved) but that share narrative function, in being, for example, a turning point within the story.
The ability to see the same (or a similar) sentence across languages makes it possible to identify the individual languages’ available tools for expressing similar material.
We have also associated a concordancer with the aligned corpus, which means that we can look for specific morphemes or lexemes and then compare them across languages.
For more details on the technical set-up, you can see our paper presented at LREC 2012, in a workshop on Building and Using Comparable Corpora.