Inter Annotator Agreement Sample Clauses

Inter Annotator Agreement. For most tasks, Xxxxx’x Kappa is reported as a measure of IAA, and is consid- ered the standard measure (XxXxxx, 2012). But for Named Entity Recognition, Kappa is not the most relevant measure, as noted in multiple studies (Xxxxxxxx & Xxxxxxxxxx, 2005; Xxxxxx et al., 2011). This is because Kappa needs the num- ber of negative cases, which isn’t known for named entities. There is no known number of items to consider when annotating entities, as they are a sequence of tokens. A solution is to calculate the Kappa on the token level, but this has two associated problems. Firstly, annotators do not annotate words individually, but look at sequences of one or more tokens, so this method does not reflect the annotation task very well. Secondly, the data is extremely unbalanced, with the un-annotated tokens (labelled "O") vastly outnumbering the actual entities, un- fairly increasing the Kappa score. A solution is to only calculate the Kappa for tokens where at least one annotator has made an annotation, but this tends to underestimate the IAA. Because of these issues, the pairwise F1 score calculated without the O label is usually seen as a better measure for IAA in Named Entity 42 CHAPTER 3. DATA SET Xxxxx’x Kappa on all tokens 0.82 Xxxxx’x Kappa on annotated tokens only 0.67 F1 score 0.95 Table 3.4: Inter-annotator agreement measures on 100 sentence test document. Calculated by doing pairwise comparisons between all combinations of annotators and averaging the results. Recognition (Xxxxxxx et al., 2012). However, as the token level Kappa scores can also provide some insight, we provide all three measures but focus on the F1 score. The scores are provided in Table 3.4. These scores are calculated by averaging the results of pairwise comparisons across all annotators. We also cal- culated these scores by comparing all the annotators against the annotations we did ourselves, and obtained the same F1 score and slightly lower Kappa (-0.02).
AutoNDA by SimpleDocs
Inter Annotator Agreement. ON ANNOTATION EFFORT OF XXXX ET AL. (2003) Xxxx et al. (2003) used Xxxxx et al.’s (1999) kappa statistic methodologies to measure various aspects of the inter-annotator agreement on their RST based corpus. Five topics were presented to fully cover the typical agreement issue of those kinds of corpora. The first topic deals with unit segmentation and the rest of them suggest methodologies for the issues emerging with the hierarchical structure of the corpora. Essentially, in all the methodologies for hierarchical aspects, hierarchical structure was flattened to a linear table by considering each possible segment pairs as units which constitute the source data to compute the kappa statistic. The following is a suitable example, which is a modified portion of a sample annotation from the study of Xxxxx et al. (1999), to clarify the claim above. In Figure 4, there are two nuclearity segmentation examples for two levels that represent two hierarchical discourse structures of the same text: Segmentation 1 N N S N S 1 0 N S Segmentation 2 Figure 4 Two sample hierarchical RST discourse structures for the same text. (N=Nucleus, S=Satellite) As a result of flattening, the following data table is constructed from the discourse structure above: Table 5 Data table of Figure 4 Segment Segmentation 1 Segmentation 2 [0,0] none N [0,1] N N [0,2] N None [1,1] none S [1,2] none None [2,2] S S The constructed agreement table is used as the input to the kappa statistic. For this sample the attributes of the kappa statistic are 2 annotators (Segmentation 1, Segmentation 2), 3 categories (N, S, none), and 9 samples (segment pairs). In the light of this explanation, five inter-annotator agreement aspects are as follows:
Inter Annotator Agreement. The need to ascertain the agreement and reliabil- ity between coders for segmentation was recognized − 3Georgescul et al. (2006, p. 48) note that both FPs and FNs are weighted by 1/N−k, and although there are “equiprobable possibilities to have a [FP] in an interval of k units”, “the total number of equiprobable possibilities to have a [FN] in an inter- val of k units is smaller than (N k)”, making the interpretation of a full miss as a FN less probable than as a FP. by Passonneau and Xxxxxx (1993), who adapted the percentage agreement metric by Xxxx et al. (1992,
Inter Annotator Agreement. Similarity alone is not a sufficiently insightful mea- sure of reliability, or agreement, between coders.
Inter Annotator Agreement. Table 3.3 show the overall statistics of the FriendsQA dataset. There is a total of 1,222 dialogues, 10,610 questions, and 21,262 answer spans in this dataset after pruning (Section 3.7). There are at least 2 answers to each question since there are 2 phases during annotation, each of which will acquire an answer to the same question. Note that annotators were not asked to paraphrase questions during the second phase of the first round (R1 in Table 3.3), so the number of questions in R1 is about twice less than ones from the other rounds. The final inter-annotator agreement scores are 81.82% and 53.55% for the F1 and exact matching scores respectively, indicating high-quality annotation in our dataset.

Related to Inter Annotator Agreement

  • Vendor Agreement (Part 1)

  • End User Agreement This publication is distributed under the terms of Article 25fa of the Dutch Copyright Act. This article entitles the maker of a short scientific work funded either wholly or partially by Dutch public funds to make that work publicly available for no consideration following a reasonable period of time after the work was first published, provided that clear reference is made to the source of the first publication of the work. Research outputs of researchers employed by Dutch Universities that comply with the legal requirements of Article 25fa of the Dutch Copyright Act, are distributed online and free of cost or other barriers in institutional repositories. Research outputs are distributed six months after their first online publication in the original published version and with proper attribution to the source of the original publication. You are permitted to download and use the publication for personal purposes. All rights remain with the author(s) and/or copyrights owner(s) of this work. Any use of the publication other than authorised under this licence or copyright law is prohibited. If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the University Library know, stating your reasons. In case of a legitimate complaint, the University Library will, as a precaution, make the material inaccessible and/or remove it from the website. Please contact the University Library through email: xxxxxxxxx@xxx.xx.xx. You will be contacted as soon as possible. University Library Radboud University

  • CFR PART 200 AND FEDERAL CONTRACT PROVISIONS EXPLANATION TIPS and TIPS Members will sometimes seek to make purchases with federal funds. In accordance with 2 C.F.R. Part 200 of the Uniform Administrative Requirements, Cost Principles, and Audit Requirements for Federal Awards (sometimes referred to as “XXXXX”),Vendor's response to the following questions labeled "2 CFR Part 200 or Federal Provision" will indicate Vendor's willingness and ability to comply with certain requirements which may be applicable to TIPS purchases paid for with federal funds, if accepted by Vendor. Your responses to the following questions labeled "2 CFR Part 200 or Federal Provision" will dictate whether TIPS can list this awarded contract as viable to be considered for a federal fund purchase. Failure to certify all requirements labeled "2 CFR Part 200 or Federal Provision" will mean that your contract is listed as not viable for the receipt of federal funds. However, it will not prevent award. If you do enter into a TIPS Sale when you are accepting federal funds, the contract between you and the TIPS Member will likely require these same certifications.

  • Vendor Agreement Signature Form (Part 1)

Draft better contracts in just 5 minutes Get the weekly Law Insider newsletter packed with expert videos, webinars, ebooks, and more!