Problem-oriented Corpus Annotation and the Hebrew Bible

What it is about

A position paper arguing that biblical scholars should add their own research-specific annotations to open datasets such as ETCBC ("problem-oriented annotation", de Haan 1984), instead of free-text notes in closed tools. From the author's experience annotating conceptual metaphors in Job (Biblia Metaphorica) and from Fort et al. (2012) on what makes annotation hard, he recommends: start from a query, not from running text, so units are pre-segmented; annotate in several passes, one word class or feature at a time; use small fixed tagsets, binary where possible, with one label for "needs more reflection"; keep annotations modular, stand-off and keyed to stable identifiers, in a format humans and machines can read; and measure quality by agreement (proportion agreeing, kappa). He also notes that no exhaustive Hebrew Bible dataset was then free for commercial use.

Ideas

• I1. When a teacher model or a person labels Hebrew phenomena for Mova (pragmatic acts, metaphor, animacy), give it pre-segmented units from a tree query and a closed, small label set with an explicit "unsure" label, one feature per pass.
• I2. Keep such labels stand-off, keyed by sent_id + token id, never edited into the CoNLL-U, so they survive reconversion of the trees.
• I3. A two-pass metaphor finder for the Torah: first label noun animacy (binary) in the dictionary, then flag clauses whose inanimate subject governs a verb that usually takes an animate subject.

For Mova

I1 and I2 are conventions for macula prag's teacher comparison and for the parse database (13. Biblical Hebrew in Mova: the tools §8, §10). I3 needs an animacy column in macula dict (10-lexicon.md, semantic fields) and a count over the trees; its output is a candidate list, not a claim.

Cite

The paper itself, not this card. BibTeX from the library's record of the work. DOI 10.7146/hn.v5i2.142730

@inproceedings{joode2019problem,
  title = {{Problem-oriented Corpus Annotation and the Hebrew Bible}},
  author = {Joode, Johan de},
  booktitle = {HIPHIL Novum 5},
  year = {2019},
  doi = {10.7146/hn.v5i2.142730},
  url = {https://doi.org/10.7146/hn.v5i2.142730}
}

References

12 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Bayerl, Petra Saskia, and Karsten Ingmar Paul. (2011) “What Determines Inter-Coder Agreement in Manual Annotations? A Meta-Analytic Investigation” Computational Linguistics 37:4, 699–725. Available online from http://www.mitpressjournals.org/doi/10.1162/COLI_a_00074 ↗
2. Carletta, J. (1996) Assessing Agreement on Classification Tasks: The Kappa Statistic. Computational Linguistics 22:2. Available online from http://homepages.inf.ed.ac.uk/jeanc/squib.pdf ↗
3. de Haan P. (1984) “Problem-oriented tagging of English corpus data.” In Corpus linguistics, J. Aarts and W. Meijs (eds.). Amsterdam: Rodopi. find
4. Fort, Karën, Adeline Nazarenko, and Sophie Rosset. (2012) “Modeling the Complexity of Manual Annotation Tasks: A Grid of Analysis.” Proc. COLING 2012 Tech. Pap. Pages 895–910, COLING 2012, Mumbai, December 2012. find
5. Leech, G. (2005) “Adding Linguistic Annotation” in Developing Linguistic Corpora: a Guide to Good Practice. M. Wynne (ed.). Oxford: Oxbow Books: 17-29. Available online from http://ota.ox.ac.uk/docu-ments/creating/dlc/ ↗
6. Mahlberg M., Stockwell P., de Joode J., Smith C., O’Donnell M. (2016). “CLiC Dickens: Novel Uses of Concordances for the Integration of Corpus Stylistics and Cognitive Poetics.” Corpora, 11 (3), 433-463. find
7. Manning, Christopher D., Prabhakar Ragahvan, and Hinrich Schutze. (2009) “An Introduction to Information Retrieval.” Information Retrieval. Cambridge: Cambridge University Press. Available online from http://nlp.stanford.edu/IR-book/pdf/irbookonlinereading.pdf 6 Amazon’s Mechanical Turk can make this even more scalable. McEnery, Tony, and Andrew. ↗
8. Hardie. (2012) Corpus Linguistics Method, Theory and Practice. Cambridge: Cambridge University Press. find
9. McEnery, Tony, and Andrew Wilson. (2011) Corpus Linguistics: An Introduction. 2nd edition. Edinburgh: Edinburgh University Press. find
10. McIntyre, Dan. (2007) “Trusting the Text: Corpus Linguistics and Stylistics.” International Journal of Corpus Linguistics 12:4, 563–75. find
11. Pragglejaz Group. (2007). “MIP: A Method for Identifying Metaphorically Used Words in Discourse.” Metaphor and Symbol 22:1, 1-39. find
12. Sinclair, John. (2004) Trust the Text: Language, Corpus and Discourse. London: Routledge, 2004. find

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