Guide the Many-to-One Assignment: Open Information Extraction via I o U -aware Optimal Transport (2023)

Abstract: Open Information Extraction (OIE) seeks to extract structured information from raw text without the limitations of close ontology. Recently, the detection-based OIE methods have received great attention from the community due to their parallelism. However, as the essential step of those models, how to assign ground truth labels to the parallelly generated tuple proposals remains under-exploited. The commonly utilized Hungarian algorithm for this procedure is restricted to handling one-to-one assignment among the desired tuples and tuple proposals, which ignores the correlation between proposals and affects the recall of the models. To solve this problem, we propose a dynamic many-to-one label assignment strategy named IOT. Concretely, the label assignment process in OIE is formulated as an Optimal Transport (OT) problem. We leverage the intersection-over-union (IoU) as the assignment quality measurement, and convert the problem of finding the best assignment solution to the one of solving the optimal transport plan by maximizing the IoU values. To further utilize the knowledge from the assignment, we design an Assignment-guided Multi-granularity loss (AM) by simultaneously considering word-level and tuple-level information. Experiment results show the proposed method outperforms the state-of-the-art models on three benchmarks.

## introduction open information extraction (oie) aims to extract structured information from the given text without the restriction of pre-defined ontology schema, and it is typically formed as a tuple ⟨subject, relation, object⟩ @xcite . for example, given the sentence "dr. pim played for ireland against england", an oie system needs to extract ⟨dr. pim, (many prs to one gt) input sentence: dr. pim played for ireland against england ## method in this section, we first introduce the process of the detection-based oie model and then present how we formulate the label assignment process in oie as an iou-aware optimal transport (ot) problem.