Petrarch 2 : Petrarcher
February 23, 2016 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Clayton Norris
arXiv ID
1602.07236
Category
cs.CL: Computation & Language
Citations
6
Venue
arXiv.org
Last Checked
5 months ago
Abstract
PETRARCH 2 is the fourth generation of a series of Event-Data coders stemming from research by Phillip Schrodt. Each iteration has brought new functionality and usability, and this is no exception.Petrarch 2 takes much of the power of the original Petrarch's dictionaries and redirects it into a faster and smarter core logic. Earlier iterations handled sentences largely as a list of words, incorporating some syntactic information here and there. Petrarch 2 now views the sentence entirely on the syntactic level. It receives the syntactic parse of a sentence from the Stanford CoreNLP software, and stores this data as a tree structure of linked nodes, where each node is a Phrase object. Prepositional, noun, and verb phrases each have their own version of this Phrase class, which deals with the logic particular to those kinds of phrases. Since this is an event coder, the core of the logic focuses around the verbs: who is acting, who is being acted on, and what is happening. The theory behind this new structure and its logic is founded in Generative Grammar, Information Theory, and Lambda-Calculus Semantics.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Computation & Language
๐
๐
Old Age
๐
๐
Old Age
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
๐
๐
Old Age
XLNet: Generalized Autoregressive Pretraining for Language Understanding
๐ฎ
๐ฎ
The Ethereal
Effective Approaches to Attention-based Neural Machine Translation
๐
๐
Old Age
A large annotated corpus for learning natural language inference
๐
๐
Old Age
HellaSwag: Can a Machine Really Finish Your Sentence?
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
๐ป
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
๐ป
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
๐ป
Ghosted