Nested Mention Recognition

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

2 leaderboard tables shown for this task, 2 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

4 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

10 shown of 10 papers with code (11 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• A Unified MRC Framework for Named Entity Recognition
  25 Oct 2019 8 repositories listed Syntology ran 2 of 5 samples · 3 unverified · 2 pointer-only (licence)
  Instead of treating the task of NER as a sequence labeling problem, we propose to formulate it as a machine reading comprehension (MRC) task.
• Nested Named Entity Recognition via Second-best Sequence Learning and Decoding
  5 Sep 2019 3 repositories listed
  When an entity name contains other names within it, the identification of all combinations of names can become difficult and expensive.
• Bipartite Flat-Graph Network for Nested Named Entity Recognition
  1 May 2020 1 repository listed
  In this paper, we propose a novel bipartite flat-graph network (BiFlaG) for nested named entity recognition (NER), which contains two subgraph modules: a flat NER module for outermost entities and a graph module for all…
• Neural Architectures for Nested NER through Linearization
  19 Aug 2019 1 repository listed
  We propose two neural network architectures for nested named entity recognition (NER), a setting in which named entities may overlap and also be labeled with more than one label.
• Merge and Label: A novel neural network architecture for nested NER
  30 Jun 2019 1 repository listed
  Named entity recognition (NER) is one of the best studied tasks in natural language processing.
• Multi-Grained Named Entity Recognition
  20 Jun 2019 1 repository listed
  This paper presents a novel framework, MGNER, for Multi-Grained Named Entity Recognition where multiple entities or entity mentions in a sentence could be non-overlapping or totally nested.
• Sequence-to-Nuggets: Nested Entity Mention Detection via Anchor-Region Networks
  10 Jun 2019 1 repository listed
  In this paper, we propose to resolve this problem by modeling and leveraging the head-driven phrase structures of entity mentions, i.
• Neural Segmental Hypergraphs for Overlapping Mention Recognition
  3 Oct 2018 1 repository listed
  In this work, we propose a novel segmental hypergraph representation to model overlapping entity mentions that are prevalent in many practical datasets.
• A Neural Transition-based Model for Nested Mention Recognition
  3 Oct 2018 1 repository listed
  It is common that entity mentions can contain other mentions recursively.
• A Neural Layered Model for Nested Named Entity Recognition
  1 Jun 2018 1 repository listed
  Each flat NER layer is based on the state-of-the-art flat NER model that captures sequential context representation with bidirectional Long Short-Term Memory (LSTM) layer and feeds it to the cascaded CRF layer.

Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.