Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
This map shows the geographic impact of Kira Griffitt's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kira Griffitt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kira Griffitt more than expected).
This network shows the impact of papers produced by Kira Griffitt. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kira Griffitt. The network helps show where Kira Griffitt may publish in the future.
Co-authorship network of co-authors of Kira Griffitt
This figure shows the co-authorship network connecting the top 25 collaborators of Kira Griffitt.
A scholar is included among the top collaborators of Kira Griffitt based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Kira Griffitt. Kira Griffitt is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
13 of 13 papers shown
1.
Strassel, Stephanie, Ann Bies, Zhiyi Song, et al.. (2019). Corpus Building for Low Resource Languages in the DARPA LORELEI Program. 48–55.5 indexed citations
2.
Griffitt, Kira, et al.. (2018). Simple Semantic Annotation and Situation Frames: Two Approaches to Basic Text Understanding in LORELEI. Language Resources and Evaluation.3 indexed citations
3.
O’Gorman, Tim, et al.. (2018). AMR Beyond the Sentence: the Multi-sentence AMR corpus. International Conference on Computational Linguistics. 3693–3702.22 indexed citations
4.
Bonial, Claire, Kira Griffitt, Ulf Hermjakob, et al.. (2018). Abstract Meaning Representation of Constructions: The More We Include, the Better the Representation.. Language Resources and Evaluation.6 indexed citations
5.
Griffitt, Kira & Stephanie Strassel. (2016). The Query of Everything: Developing Open-Domain, Natural-Language Queries for BOLT Information Retrieval.. Language Resources and Evaluation. 3741–3747.1 indexed citations
Bonial, Claire, Shu Cai, Kira Griffitt, et al.. (2013). Proceedings of the 7th Linguistic Annotation Workshop and Interoperability with Discourse.86 indexed citations
9.
Strassel, Stephanie, et al.. (2012). Linguistic Resources for Entity Linking Evaluation: from Monolingual to Cross-lingual. Language Resources and Evaluation. 3098–3105.4 indexed citations
10.
Ellis, Joe, et al.. (2012). Linguistic Resources for 2012 Knowledge Base Population Evaluations. Theory and applications of categories.13 indexed citations
11.
Wright, Jonathan, et al.. (2012). Annotation Trees: LDC's customizable, extensible, scalable, annotation infrastructure. Language Resources and Evaluation. 479–485.7 indexed citations
12.
Ellis, Joe, et al.. (2011). Linguistic Resources for 2011 Knowledge Base Population Evaluation.. Theory and applications of categories.3 indexed citations
13.
Ji, Heng, Ralph Grishman, Hoa Trang Dang, Kira Griffitt, & Joe Ellis. (2010). Overview of the TAC 2010 Knowledge Base Population Track.251 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.