Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Guan, Saiping"'
Sparse Knowledge Graphs (KGs), frequently encountered in real-world applications, contain fewer facts in the form of (head entity, relation, tail entity) compared to more populated KGs. The sparse KG completion task, which reasons answers for given q
Externí odkaz:
http://arxiv.org/abs/2407.18556
Autor:
Liu, Yantao, Li, Zixuan, Jin, Xiaolong, Guo, Yucan, Bai, Long, Guan, Saiping, Guo, Jiafeng, Cheng, Xueqi
The Knowledge Base Question Answering (KBQA) task aims to answer natural language questions based on a given knowledge base. Recently, Large Language Models (LLMs) have shown strong capabilities in language understanding and can be used to solve this
Externí odkaz:
http://arxiv.org/abs/2310.14174
Autor:
Ren, Weicheng, Li, Zixuan, Jin, Xiaolong, Bai, Long, Su, Miao, Liu, Yantao, Guan, Saiping, Guo, Jiafeng, Cheng, Xueqi
Nested Event Extraction (NEE) aims to extract complex event structures where an event contains other events as its arguments recursively. Nested events involve a kind of Pivot Elements (PEs) that simultaneously act as arguments of outer-nest events a
Externí odkaz:
http://arxiv.org/abs/2309.12960
Event Causality Identification (ECI) aims to identify causal relations between events in unstructured texts. This is a very challenging task, because causal relations are usually expressed by implicit associations between events. Existing methods usu
Externí odkaz:
http://arxiv.org/abs/2305.12792
Hyper-relational facts, which consist of a primary triple (head entity, relation, tail entity) and auxiliary attribute-value pairs, are widely present in real-world Knowledge Graphs (KGs). Link Prediction on Hyper-relational Facts (LPHFs) is to predi
Externí odkaz:
http://arxiv.org/abs/2305.06104
Script is a kind of structured knowledge extracted from texts, which contains a sequence of events. Based on such knowledge, script event prediction aims to predict the subsequent event. To do so, two aspects should be considered for events, namely,
Externí odkaz:
http://arxiv.org/abs/2212.08287
Autor:
Li, Zixuan, Hou, Zhongni, Guan, Saiping, Jin, Xiaolong, Peng, Weihua, Bai, Long, Lyu, Yajuan, Li, Wei, Guo, Jiafeng, Cheng, Xueqi
A Temporal Knowledge Graph (TKG) is a sequence of KGs with respective timestamps, which adopts quadruples in the form of (\emph{subject}, \emph{relation}, \emph{object}, \emph{timestamp}) to describe dynamic facts. TKG reasoning has facilitated many
Externí odkaz:
http://arxiv.org/abs/2210.09708
Autor:
Li, Zixuan, Guan, Saiping, Jin, Xiaolong, Peng, Weihua, Lyu, Yajuan, Zhu, Yong, Bai, Long, Li, Wei, Guo, Jiafeng, Cheng, Xueqi
A Temporal Knowledge Graph (TKG) is a sequence of KGs corresponding to different timestamps. TKG reasoning aims to predict potential facts in the future given the historical KG sequences. One key of this task is to mine and understand evolutional pat
Externí odkaz:
http://arxiv.org/abs/2203.07782
Autor:
Guan, Saiping, Cheng, Xueqi, Bai, Long, Zhang, Fujun, Li, Zixuan, Zeng, Yutao, Jin, Xiaolong, Guo, Jiafeng
Besides entity-centric knowledge, usually organized as Knowledge Graph (KG), events are also an essential kind of knowledge in the world, which trigger the spring up of event-centric knowledge representation form like Event KG (EKG). It plays an incr
Externí odkaz:
http://arxiv.org/abs/2112.15280
Scripts are structured sequences of events together with the participants, which are extracted from the texts.Script event prediction aims to predict the subsequent event given the historical events in the script. Two kinds of information facilitate
Externí odkaz:
http://arxiv.org/abs/2110.15706