CMAR


CAMR

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Sample sentence in Little Prince(Chinese Translation)
# ::id test_amr.1542 ::2015-11-14 22:34:00
# ::en And there is sweetness in the laughter of all the stars .
# ::snt 这时 , 所有 的 星星 都 在 柔情 地 轻声 笑 着 。
(x1 / 笑-01 laugh
      :arg0  (x2 / 星星 star
            :mod  (x3 / 所有 all))
      :time  (x4 / 这时 now)
      :manner  (x5 / 柔情 sweetness)
      :manner  (x6 / 轻声 soft sound))






Links

The Chinese Abstract Meaning Representation(CAMR) Bank is a set of Chinese sentences paired with simple, readable semantic representations.

We hope that it will spur new research in natural language understanding, generation, and translation.

What's new?

  • Public release V2.0 (Nov. 14, 2016) of the Little Prince(Chinese Translation). Sentenes aligned to ISI's English translation version.
    • Annotation: Standard split: 145 dev AMRs, 1274 training AMRs, 143 test AMRs
  • Public release of CTBWEB corpus, extracted from CTB8.0.
    • Annotation (5015 AMRs)
  • CAMR Guidelines  V2.0
  • CAMR Annotation toolkit V2.0 (support word to concept alignment demo vedio).
The Chinese AMR Bank is manually constructed by human annotators at:
  • Brandeis University, Waltham, USA
  • Nanjing Normal University, Nanjing, China.
People
      Nianwen Xue, Chuan Wang, Yuchen Zhang, Bin Li, Lijun Bu, Yuan Wen, Li Song, Rubing Dai, Junsheng Zhou, Weiguang Qu.

Papers
  • "Annotating the Little Prince with Chinese AMRs" ( Bin Li, YuanWen, Lijun Bu,Weiguang Qu, Nianwen Xue.) LAW-2016, Aug 11, 2016, Berlin, Germany. PDF
  • "A Comparative Analysis of the AMR Graphs from English and Chinese corpus of the Little Prince" ( BinLi, YuanWen, Lijun Bu, Nianwen Xue). CCL2016 ( in Chinese, accepted), Yantai, China, 2016. 
  • "Boosting Transition-based AMR Parsing with Refined Actions and Auxiliary Analyzers" (C. Wang, N. Xue, and S. Pradhan), Proc. ACL, 2015.PDF
  • "A Transition-based Algorithm for AMR Parsing" (Chuan Wang, Nianwen Xue, Sameer Pradhan), Proc. NAACL, 2015.PDF
  • "Notan Interlingua, but Close: Comparison of English AMRs to Chinese and Czech" (N. Xue, O. Bojar, J. Hajic, M. Palmer, Z. Uresova, X. Zhang). Proc. LREC, 2014.PDF



Questions or comments? Please contact libin.njnu@gmail.com