The art of doing science: alignments in historical linguistics

In the past two years, during which I have been writing for this blog, I have often tried to emphasize the importance of alignments in historical linguistics — alignment involves explicit decisions about which characters / states are cognate (and can thus be aligned in a data table). I have also often mentioned that explicit alignments are still rarely used in the field.

To some degree, this situation is frustrating, since it seems so obvious that scholars align data in their head, for example, whenever they write etymological dictionaries and label parts of a word as irregular, not fulfilling their expectations when assuming regular sound change (in the sense in which I have described it before). It is also obvious that linguists have been trying to use alignments before (even before biologists, as I tried to show in this earlier post), but for some reason, they never became systematized.

As an example for the complexity of alignment analyses in historical linguistics, consider the following figure, which depicts both an early version of an alignment (following Dixon and Kroeber 1919), and a "modern" version of the dame data. For the latter, I used the EDICTOR (http://edictor.digling.org), a software tool that I have been developing during recent years, and which helps linguists to edit alignments in a consistent way (List 2017). The old version on the left has been modified in such a way that it becomes clearer what kind of information the authors tried to convey (for the original, see my older post), while the EDICTOR version contains some markup that is important for linguistics, which I will discuss in more detail below.

Figure 1: Alignments from Dixon and Kroeber (1919) in two flavors

If we carefully inspect the first alignment, it becomes evident that the scholars did not align the data sound by sound, but rather morpheme by morpheme. Morphemes are those parts in words that are supposed to bear a clear-cut meaning, even when taken in isolation, or when abstracting from multiple words. The plural-ending -s in English, for example, is a morpheme that has the function to indicate the plural (compare horse vs. horses, etc.). In order to save space, the authors used abbreviations for the language group names and the names for the languages themselves.

The authors have further tried to save space by listing identical words only once, but putting two entries, separated by a comma, in the column that I have labelled "varieties". If you further compare the entries for NW (=North-Western Maidu) and NE/S (=North-Eastern Maidu and Southern Maidu), you can see that the first entry has been swapped: the tsi’ in tsi’-bi in NW is obviously better compared with the tsi in NE/S bi-tsi rather than comparing bi in NE with tsi in NE/S. This could be a typographical error, of course, but I think it is more likely that the authors did not quite know how to handle swapped instances in their alignment.

In the EDICTOR representation of the alignment, I have tried to align the sounds in addition to aligning the morphemes. My approach here is rather crude. In order to show which sounds most likely share a common origin, I extracted all homologous morphemes, aligned them in such a way that they occur in the same column, and then stripped off the remaining sounds by putting a check-mark in the IGNORE column on the bottom of the EDICTOR representation. When further analyzing these sound correspondences with some software, like the LingPy library (List et al. 2017), all sounds that occur in the IGNORE column will be ignored. Correspondences will then only be calculated for the core part of this alignment, namely the two columns that are left over, in the center of the alignment.

In many cases, this treatment of sound correspondences and homologous words in alignments is sufficient, and also justified. If we want to compare the homologous (cognate) parts across words in different languages, we can't align the words entirely. Consider, for example, the German verb gehen [geːən] and its English counterpart go [gɔu]. German regularly adds the infinitive ending -en to each verb, but English has long ago dropped all endings on verbs apart from the -s in the third person singular (compare go vs. goes). Comparing the whole of the verbs would force us to insert gaps for the verb ending in German, which would be linguistically not meaningful, as those have not been "gapped" in English, but lost in a morphological process by which all endings of English verbs were lost.

There are, however, also cases that are more complicated to model, especially when dealing with instances of partial cognacy (or partial homology). Compare, for example, the following alignment for words for bark (of a tree) in several dialects of the Bai language, a Sino-Tibetan language spoken in China, whose affiliation with other Sino-Tibetan languages is still unclear (data taken from Wang 2006).

Figure 2: Alignment for words for "bark" in Bai dialects

In this example, the superscript numbers represent tones, and they are placed at the end of each syllable. Each syllable in these languages usually also represents a morpheme in the sense mentioned above. That means, that each of the words is a compound of two original meanings. Comparison with other words in the languages reveals that most dialects, apart from Mazhelong, express bark as tree-skin, which is a very well-known expression that we can find in many languages of the world. If we want to analyze those words in alignments, we could follow the same strategy as shown above, and just decide for one core part of the words (probably the skin part) and ignore the rest. However, for our calculations of sound correspondences, we would loose important information, as the tree part is also cognate in most instances and therefore rather interesting. But ignoring only the unalignable part of the first syllable in Mazhelong would also not be satisfying, since we would again have gaps for this word in the tree part in Mazhelong which do not result from sound change.

The only consistent solution to handle these cases is to split the words into their morphemes, and then to align all sets of homologous morphemes separately. This can also be done in the EDICTOR tool (but it requires more effort from the scholar and the algorithms). An example is shown above, where you can see how the tool breaks the linear order in the representation of the words as we find them in the languages, in order to cluster them into sets of homologous "word-parts".

Figure 3: Alignments of partial cognates in the Bai dialects

But if we only look at the tree part of those alignments, namely the third cognate set from the left, with the ID 8, we can see a further complication, as the gaps introduced in some of the words look a little bit unsatisfying. The reason is that the j in Enqi and Tuolo may just as well be treated as a part of the initial of the syllable, and we could re-write it as dj in one segment instead of using two. In this way, we might capture the correspondence much more properly, as it is well known that those affricate initials in the other dialects ([ts, tʂ, dʐ, dʑ]) often correspond to [dj]. We could thus rewrite the alignment as shown in the next figure, and simply decide that in this situation (and similar ones in our data), we treat the d and the j as just one main sound (namely the initial of the syllables).

Figure 4: Revised alignment of "tree" in the sample

Summary and conclusions

Before I start boring those of the readers of this blog who are not linguists, and not particularly interested in details of sound change or language change, let me just quickly summarize what I wanted to illustrate with these examples. I think that the reason why linguists never really formalized alignments as a tool of analysis is that there are so many ways to come up with possible alignments of words, which may all be reasonable for any given analysis. In light of this multitude of possibilities for analysis, not to speak of historical linguistics as a discipline that often prides itself by being based on hard manual labor that would be impossible to achieve by machines, I can in part understand why linguists were reluctant to use alignments more often in their research.

Judging from my discussions with colleagues, there are still many misunderstandings regarding the purpose and the power of alignment analyses in historical linguistics. Scholars often think that alignments directly reflect sound change. But how could they, given that we do not have any ancestral words in our sample? Alignments are a tool for analysis, and they can help to identify sound change processes or to reconstruct proto-forms in unattested ancestral languages; but they are by no means the true reflection of what happened and how things changed. The are the starting point, not the end point of the analysis. Furthermore, given that there are many different ways in which we can analyze how languages changed over time, there are also many different ways in which we can analyze language data with the help of alignments. Often, when comparing different alignment analyses for the same languages, there is no simple right and wrong, just a different emphasis on the initial analysis and its purpose.

As David wrote in an email to me:

"An alignment represents the historical events that have occurred. The alignment is thus a static representation of a dynamic set of processes. This is ultimately what causes all of the representational problems, because there is no necessary and sufficient way to achieve this."

This also nicely explains why alignments in biology as well, with respect to the goal of representing homology, "may be more art than science" (Morrison 2015), and I admit that I find it a bit comforting that biology has similar problems, when it comes to the question of how to interpret an alignment analysis. However, in contrast to linguists, who have never really given alignments a chance, biologists not only use alignments frequently, but also try to improve them.

If I am allowed to have an early New Year wish for the upcoming year, I hope that along with the tools that facilitate the labor of creating alignments for language data, we will also have a more vivid discussion about alignments, their shortcomings, and potential improvements in our field.

References

• Dixon, R. and A. Kroeber (1919) Linguistic families of California. University of California Press: Berkeley.
• List, J.-M. (2017) A web-based interactive tool for creating, inspecting, editing, and publishing etymological datasets. In: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics. System Demonstrations, pp. 9-12.
• LingPy: A Python library for historical linguistics. Version 2.6. Max Planck Institute for the Science of Human History: Jena.
• Morrison, D. (2015) Molecular homology and multiple-sequence alignment: an analysis of concepts and practice. Australian Systematic Botany 28: 46-62.
• Wang, W.-Y. (2006) Yǔyán, yǔyīn yǔ jìshù \hana 語言,語音與技術 [Language, phonology and technology]. Xiānggǎng Chéngshì Dàxué: Shànghǎi 上海.