uema2lab_narrative — Retrieval Only Task

Is this a manual (human intervention) or automatic run?: automatic
Does this run leverage neural networks?: yes
Does this run leverage proprietary models in any step of the retrieval pipeline?: yes
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?: Ensemble/Fusion of First Stages
Please provide a short description of this run: We applied a hybrid search combining BM25 and dense retrieval (OpenAI text-embedding-3-small, 1536-dim) to retrieve the top-20 documents per narrative. From each document, the segment most similar in embedding space to the narrative text was selected, and the ranked document lists were thus converted into segment-level lists for evaluation. This run serves as a comparison baseline to the subquery-expansion approach. The results are compared against other runs (runid: uema2lab_rrf, uema2lab_rrf_k10, uema2lab_segment).
Please give this run a priority for inclusion in manual assessments.: 4