A Formal Framework for Linguistic Annotation (revised version)
Steven Bird, Mark Liberman
Abstract
`Linguistic annotation' covers any descriptive or analytic notations applied to raw language data. The basic data may be in the form of time functions - audio, video and/or physiological recordings - or it may be textual. The added notations may include transcriptions of all sorts (from phonetic features to discourse structures), part-of-speech and sense tagging, syntactic analysis, `named entity' identification, co-reference annotation, and so on. While there are several ongoing efforts to provide formats and tools for such annotations and to publish annotated linguistic databases, the lack of widely accepted standards is becoming a critical problem. Proposed standards, to the extent they exist, have focused on file formats. This paper focuses instead on the logical structure of linguistic annotations. We survey a wide variety of existing annotation formats and demonstrate a common conceptual core, the annotation graph. This provides a formal framework for constructing, maintaining and searching linguistic annotations, while remaining consistent with many alternative data structures and file formats.
Create a lesson
Related papers
RSI-Anything: Unlocking Recursive Self-Improvement with World Models
Taoyong Cui, Pinxian Zeng, Wanghan Xu et al.
When VLMs Destroy What They Know: Spatial Representations Fall Below Lexical Priors
Shubh Garg, Chen Shani
Structural Automata for Neural Semantic Parsing
Xiao Zhang
Task Context Shapes Component Roles in Language Models
Sovesh Mohapatra, Dani S Bassett
Can Language Models Learn When to Abstain? Policy Learning and Calibrated Answer Selection
Juan Terven, Diana-Margarita Córdova-Esparza, Ruben Gomez et al.
Error Rate is Not Enough: Costs of Augmentation in Low-Resource ASR
Katsumi Ibaraki, David Chiang