Pipeline Inspection, Visualization, and Interoperability in PyTerrier
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866915763388940288 |
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| author | Lionis, Emmanouil Georgios Macdonald, Craig MacAvaney, Sean |
| author_facet | Lionis, Emmanouil Georgios Macdonald, Craig MacAvaney, Sean |
| contents | PyTerrier provides a declarative framework for building and experimenting with Information Retrieval (IR) pipelines. In this demonstration, we highlight several recent pipeline operations that improve their ability to be programmatically inspected, visualized, and integrated with other tools (via the Model Context Protocol, MCP). These capabilities aim to make it easier for researchers, students, and AI agents to understand and use a wide array of IR pipelines. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_17502 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Pipeline Inspection, Visualization, and Interoperability in PyTerrier Lionis, Emmanouil Georgios Macdonald, Craig MacAvaney, Sean Information Retrieval PyTerrier provides a declarative framework for building and experimenting with Information Retrieval (IR) pipelines. In this demonstration, we highlight several recent pipeline operations that improve their ability to be programmatically inspected, visualized, and integrated with other tools (via the Model Context Protocol, MCP). These capabilities aim to make it easier for researchers, students, and AI agents to understand and use a wide array of IR pipelines. |
| title | Pipeline Inspection, Visualization, and Interoperability in PyTerrier |
| topic | Information Retrieval |
| url | https://arxiv.org/abs/2601.17502 |