Latin Treebanks in Review: An Evaluation of Morphological Tagging Across Time

TL;DR

This paper reviews Latin treebanks spanning 17 centuries, analyzes their annotation heterogeneity, and evaluates morphological tagging performance across time using BERT-based models, highlighting their robustness and improvements.

Contribution

It systematically reviews Latin treebanks, creates standardized annotation conversions, and introduces new time-based data splits for cross-temporal morphological tagging evaluation.

Findings

BERT-based taggers outperform previous models.

Taggers show robustness across different historical periods.

The study provides a comprehensive analysis of Latin morphological annotation coverage.

Abstract

Existing Latin treebanks draw from Latin's long written tradition, spanning 17 centuries and a variety of cultures. Recent efforts have begun to harmonize these treebanks' annotations to better train and evaluate morphological taggers. However, the heterogeneity of these treebanks must be carefully considered to build effective and reliable data. In this work, we review existing Latin treebanks to identify the texts they draw from, identify their overlap, and document their coverage across time and genre. We additionally design automated conversions of their morphological feature annotations into the conventions of standard Latin grammar. From this, we build new time-period data splits that draw from the existing treebanks which we use to perform a broad cross-time analysis for POS and morphological feature tagging. We find that BERT-based taggers outperform existing taggers while also being more robust to cross-domain shifts.