---
title: "A Double-Graph Based Framework for Frame — Zheng 2022"
description: "Frame semantic parsing takes a target word in a sentence and does three things: it picks the FrameNet frame the word evokes, finds the word's arguments…"
authors: ["Ce Zheng", "Xudong Chen", "Runxin Xu", "Baobao Chang"]
year: 2022
venue: "Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies"
source: "https://aclanthology.org/2022.naacl-main.368/"
doi: "10.18653/v1/2022.naacl-main.368"
arxiv: "2206.09158"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/papers/zheng-2022-double-graph-based-framework-frame/"
---
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# A Double-Graph Based Framework for Frame Semantic Parsing

**Authors:** [Ce Zheng](https://md.research.elamur.ai/free/authors/ce-zheng/), Xudong Chen, [Runxin Xu](https://md.research.elamur.ai/free/authors/runxin-xu/), [Baobao Chang](https://md.research.elamur.ai/free/authors/baobao-chang/) · **Year:** 2022 · **Venue:** Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2022.naacl-main.368/) · [PDF](https://aclanthology.org/2022.naacl-main.368.pdf) · [DOI 10.18653/v1/2022.naacl-main.368](https://doi.org/10.18653/v1/2022.naacl-main.368) · [arXiv 2206.09158](https://arxiv.org/abs/2206.09158) · [OpenAlex](https://openalex.org/W4283326715)

**Citations:** 13 citations (openalex-snapshot · 2026-10-14) · 7 in our library, of the 140673 papers whose bibliographies we read

## Summary
Frame semantic parsing takes a target word in a sentence and does three things: it picks the FrameNet frame the word evokes, finds the word's arguments, and labels each argument with a frame element (FE). Earlier systems usually treated these steps separately, labeled each argument on its own, and made little use of FrameNet's ontology. The authors propose KID, a parser built on two graphs. The Frame Knowledge Graph (FKG) links frames and FEs through frame relations, FE mappings and FE mentions inside definitions. An RGCN over this graph produces knowledge-aware embeddings of frames and roles in a single shared space. The Frame Semantic Graph (FSG) stores the structure parsed so far. Starting from the target and its predicted frame, the decoder adds one argument–role pair per step, so each decision depends on the earlier ones. On FN 1.5 and FN 1.7, KID sets a new state of the art, gaining up to 1.7 F1 over the best previous system. Zero- and few-shot tests suggest FKG helps transfer knowledge to rarely seen frames.

## Key points
- FKG is a heterogeneous graph with four edge types: frame–FE, frame–frame, inter-frame FE–FE (from FE mappings) and intra-frame FE–FE (from definitions). It is encoded with RGCN. FEs that share a name also share their initial embedding.
- The sentence encoder combines a BiLSTM with a GCN over the dependency tree. Argument boundaries are predicted with pointer networks conditioned on the current partial FSG.
- Evaluation is on FN 1.5 and FN 1.7, where KID improves the previous state of the art by up to 1.7 F1. Code is available at github.com/PKUnlp-icler/KID.
- Ablations show the name-based embedding sharing is useful. Even without it, removing FKG costs about 0.9 points.
- The transfer experiment holds out all instances of the target "get" (frames Arriving, Getting, Transition_to_state) and trains with K = 0, 4, 16 or 32 examples. Without FKG the model performs much worse in the zero-shot case.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

Fields: [Linguistics & languages](https://md.research.elamur.ai/free/shelves/linguistics/)

## Cite

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{zheng2022double,
  title = {{A Double-Graph Based Framework for Frame Semantic Parsing}},
  author = {Zheng, Ce and Chen, Xudong and Xu, Runxin and Chang, Baobao},
  booktitle = {Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
  year = {2022},
  doi = {10.18653/v1/2022.naacl-main.368},
  eprint = {2206.09158},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.18653/v1/2022.naacl-main.368}
}
```

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