DSSM | Learning Deep Structured Semantic Models for Web Search | Natural Language Processing library

// Task 1 -- the main thread
        SimilarityResponse w2vResponse = questionClassifier.compute(questionInfo);

        // Task 2
        String sku = questionInfo.getSku();
        String question = questionInfo.getQuestion();
        Callable dssmTask = () -> this.dssmCompute(sku, question);
        Future dssmService = executorService.submit(dssmTask);
        ResponseList dssmResponse;
        try {
            LOGGER.info("start dssm ... {} ", question);
            dssmResponse = dssmService.get(Parameters.getParserTimeLimit(), TimeUnit.MILLISECONDS);
            LOGGER.info("dssmResponse ... {} ", dssmResponse);
        } catch (ExecutionException | InterruptedException e) {
            LOGGER.warn("ExecutionException | InterruptedException");
            e.printStackTrace();
        } catch (TimeoutException te) {
            dssmService.cancel(true);
            LOGGER.warn("DSSM time out for {} {}", sku, question);
        }

        // Task 3
        Callable stsTask = () -> this.stsCompute(sku, question);
        Future stsService = executorService.submit(stsTask);
        ResponseList stsResponse;
        try {
            LOGGER.info("start sts ... {} ", question);
            stsResponse = stsService.get(Parameters.getParserTimeLimit(), TimeUnit.MILLISECONDS);
            LOGGER.info("stsResponse ... {} ", stsResponse);
        } catch (ExecutionException | InterruptedException e) {
            LOGGER.warn("ExecutionException | InterruptedException");
            e.printStackTrace();
        } catch (TimeoutException te) {
            stsService.cancel(true);
            LOGGER.warn("STS time out for {} {}", sku, question);
        }

        // Last step == do something for above
        SimilarityResponse ensemble = new SimilarityResponse();
        return ensemble;