bm25_NITA_JH — Retrieval Only Task

Is this a manual (human intervention) or automatic run?: automatic
Does this run leverage neural networks?: no
Does this run leverage proprietary models in any step of the retrieval pipeline?: no
Does this run leverage open-weight LLMs (> 5B parameters) in any step of the retrieval pipeline?: no
Does this run leverage smaller open-weight language models in any step of the retrieval pipeline?: no
Was this run padded with results from a baseline run?: no
What would you categorize this run as?: Traditional Only
Please provide a short description of this run: This run applies a BM25 retrieval pipeline using Pyserini over the MS MARCO v2.1 segmented corpus. A Lucene index was constructed with positional information, document vectors, and raw text storage enabled, and queries were preprocessed into TSV format for compatibility. Retrieval was performed with BM25 (k1=1.2, b=0.75), returning the top-100 ranked segments per query, and outputs were generated in standard TREC run file format.
Please give this run a priority for inclusion in manual assessments.: 2