[PDF] Top 20 Annotation Artifacts in Natural Language Inference Data

... for natural language in- ference are created by presenting crowd work- ers with a sentence (premise), and asking them to generate three new sentences (hypotheses) that it entails, contradicts, or is ... See full document

... the Data class for the Facebook API, we found only 2 (9%) instances where the specifications inferred by our approach completely matched the code contracts written by Rubinger et ...the Data class of the ... See full document

... SNLI and MultiNLI We evaluated our model on the natural language inference task over SNLI and MultiNLI datasets. Table 2 shows the results on SNLI dataset of our model with other published models. ... See full document

... Similarly, top keywords for availability include “run”, “availability”, “retain”, “time”, “destroy”, “retention”, and “real- time”. Like identification/authentication, no grammatical pattern exists for availability ... See full document

... less data (570k compared to 64M sentences) but with high-quality supervision from the SNLI dataset, we are able to consistently outperform the results obtained by SkipThought ... See full document

... into data-driven models for automatic natural language understanding ...in language technology for many applications, most notably information retrieval, machine translation, and speech ... See full document

... Attempts to learn generic encoders with dis- criminative objectives were considered by Nie et al. (2017) and Logeswaran and Lee (2018) who replaced the decoder of skip-thoughts with classi- fication tasks based on ... See full document

... [5] proposed a matching aggregation framework which is a multiway attention network (MwAN). Their model applies the attention mechanism at the word level which leads to improve the matching between words in two ... See full document

... Figure 1: The Multiple Premise Entailment Task Similar to the SICK and SNLI datasets (Marelli et al., 2014; Bowman et al., 2015), each premise sentence in our data is a single sentence describ- ing everyday ... See full document

... Artificially generated datasets have also been used extensively to gain analytic insights into what models are learning. These methods have the ad- vantage that the complexity of individual exam- ples can be precisely ... See full document

... 4. Little training data is available. MT align- ment models are typically trained in unsu- pervised fashion, inducing lexical correspon- dences from massive quantities of sentence- aligned bitexts. While NLI ... See full document

... The results of this validation process are sum- marized in Table 3. Nearly all of the examples received a majority label, indicating broad con- sensus about the nature of the data and categories. The gold-labeled ... See full document

... Stanford inference scores by +∆ or −∆, depending on whether or not NatLog predicts ...development data, its use on test data is fully ...development data gave good results on test ... See full document

... her/his annotation process for eliciting useful information for natural language processing (NLP) ...Text annotation is essential for machine learning-based NLP where annotated texts are used ... See full document

... for training, 9,842 for development, and 9,824 for testing. We use the tokenized sentences from the non-binary parse provided in the dataset and prepend each sentence with a “NULL” token. During training, each sentence ... See full document

... test data), but the dif- ference is small and the complexity of bi-LSTM is much higher than ...test data, which is still better than previously reported state of the ... See full document

... ESIM’s reasonably strong performance on Dia- logue NLI suggests that the model may be useful in a downstream task - a claim which we verify in Experiment 5.1. However, there is also room for improvement. In particular, ... See full document

... first language with excellent command of ...an inference (example ...of inference is to query individual participants directly to indicate their degree of belief (rather than using 3 categories used ... See full document

... to natural language inference going back to Fyodorov et ...of inference, but to cope with NLI datasets we augment replacement with rules of natural logic (van Benthem, 1986), and with a ... See full document

... Consider two competitive machine learn- ing models, one of which was considered state-of-the art, and the other a competi- tive baseline. Suppose that by just permut- ing the examples of the training set, say by ... See full document