We implemented two such models, denoted DMM LS and DPM LS , by replacing the component that assigns argument labels with one that relies on LS.
as in §4.3, we compute the cosine similarity between the composite LS vectors of the question text and each marker argument (in DMM) or EDU (in DPM), and label the corresponding answer segment QSEG if this score is higher than a threshold, or OTHER otherwise.