---
title: "Graph-Augmented LLMs for Swiss MP Ideology Prediction (2026)"
description: "The authors present PG-RAG, a retrieval-augmented pipeline that queries a Swiss political knowledge graph and adds the… 53 references."
authors: ["Yifei Yuan", "Luis Salamanca", "Sophia Schlosser", "Laurence Brandenberger"]
year: 2026
venue: "Proceedings of the 11th Edition of the Swiss Text Analytics Conference"
source: "https://aclanthology.org/2026.swisstext-1.12/"
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/en/papers/yuan-2026-graph-augmented-llms-swiss-mp/"
---
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# Graph-Augmented LLMs for Swiss MP Ideology Prediction

**Authors:** [Yifei Yuan](https://md.research.elamur.ai/free/en/authors/yifei-yuan/), Luis Salamanca, Sophia Schlosser and Laurence Brandenberger · **Year:** 2026 · **Venue:** [Proceedings of the 11th Edition of the Swiss Text Analytics Conference](https://md.research.elamur.ai/free/en/venues/swisstext/) ([Edition of the Swiss Text Analytics Conference 2026](https://md.research.elamur.ai/free/en/venues/swisstext/2026/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2026.swisstext-1.12/) · [PDF](https://aclanthology.org/2026.swisstext-1.12.pdf) · [OpenAlex](https://openalex.org/W7160563153)

**Citations:** 0 citations (OpenAlex, 2026-10-14)

## Summary
Political scientists need to place Members of Parliament on an ideological scale. Recent LLM-based estimators mostly treat each MP as an isolated source of text and overlook the relational structure of parliament, such as committees, party groups and co-sponsored proposals. The authors present PG-RAG, a retrieval-augmented pipeline that queries a Swiss political knowledge graph and adds the retrieved subgraph to the LLM prompt alongside basic MP metadata. The graph is built from the Bulletin of the Swiss Parliament. They define three subgraph types: speech-centric, MP-centric and pursuit-centric. Each subgraph is passed to the model in one of two forms, either as an LLM-written summary of serialized triplets or as a raw list of nodes and links. Compared with zero-shot and few-shot LLM baselines of various sizes, graph context consistently improves ideology predictions, and the smaller model benefits most. Left-leaning MPs, especially Social Democrats, remain hard to place because models tend to predict moderate scores for them. The study shows that domain-specific relational knowledge can strengthen computational models of legislative behavior.

## Key points
- The knowledge graph covers legislative periods 48–51 (2007–2023). It is published by Brandenberger et al. (2024) and its construction is described in Salamanca et al. (2024). Its core entities include Person, Pursuit, Speech, Party, Committee and Canton.
- The six variants combine three subgraph types with two encodings: SP-S/R, MP-S/R and PR-S/R. SP is purely textual, MP spans 1-hop institutional relations, and PR goes up to 2 hops through sponsored and co-sponsored Pursuits.
- Reported gains across RAG settings are 16.4–22.4% for the smaller Qwen-8B and 8.7–16.5% for GPT-5.
- The pursuit-based setting worked best for Qwen-8B but gave GPT-5 its smallest gain (8.7%). This suggests larger models depend less on external structure.
- In the case study, a Social Democrat MP has a ground-truth score of 9.0. PG-RAG (MP-S) predicted 7.1, closer than GPT-5's 6.5.

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

## Institutions

- [ETH Zurich](https://md.research.elamur.ai/free/en/universities/eth-zurich/) — University, Zurich, Switzerland · 84 works · 9,181 citations
- [University of Zurich](https://md.research.elamur.ai/free/en/universities/university-of-zurich/) — University, Zurich, Switzerland · 80 works · 12,260 citations
- [Zurich University of Teacher Education](https://md.research.elamur.ai/free/en/universities/zurich-university-of-teacher-education/) — University, Zurich, Switzerland · 3 works · 5 citations
- [Swiss Data Science Center](https://md.research.elamur.ai/free/en/universities/swiss-data-science-center/) — University, Zurich, Switzerland · 2 works · 1 citation

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## Cite

Cite as: Yifei Yuan, Luis Salamanca, Sophia Schlosser and Laurence Brandenberger. 2026. Graph-Augmented LLMs for Swiss MP Ideology Prediction. Proceedings of the 11th Edition of the Swiss Text Analytics Conference.

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

```bibtex
@inproceedings{yuan2026graph,
  title = {{Graph-Augmented LLMs for Swiss MP Ideology Prediction}},
  author = {Yifei Yuan, Luis Salamanca, Sophia Schlosser and Laurence Brandenberger},
  booktitle = {Proceedings of the 11th Edition of the Swiss Text Analytics Conference},
  year = {2026},
  url = {https://aclanthology.org/2026.swisstext-1.12/}
}
```

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*Updated 2 November 2026*