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README.md

@@ -19,8 +19,43 @@ Based on the review, we suggest promising research directions for the future. Ou
 (3) We propose several research directions that can be developed in the future.
 
 ## *👋 News!*
+- We conducted the development of knowledge extraction toolkits such as [DEEPKE](https://github.com/zjunlp/DeepKE) and [PromptKG](https://github.com/zjunlp/PromptKG).
+- Due to the rise of generative extraction methods in the NLP community，we summarize recent progress in generative KGC.
 - Congratulations! Our work has been accepted by the EMNLP2022 main conference.
-- We will release our paper on arivx soon!
+- We release our paper on arivx.
+
+### 🚩Citation 
+If you find this survey useful for your research, please consider citing
+```
+@misc{https://doi.org/10.48550/arxiv.2210.12714,
+  doi = {10.48550/ARXIV.2210.12714},
+  url = {https://arxiv.org/abs/2210.12714},
+  author = {Ye, Hongbin and Zhang, Ningyu and Chen, Hui and Chen, Huajun},
+  title = {Generative Knowledge Graph Construction: A Review},
+  publisher = {arXiv},
+  year = {2022},
+}
+```
+
+## ⚓️ Preliminary on Knowledge Graph Construction
+
+Knowledge Graph Construction mainly aims to extract structural information from unstructured texts, 
+such as Named Entity Recognition (NER), Relation Extraction (RE), Event Extraction (EE), Entity Linking (EL), and Knowledge Graph Completion (KGC).
+
+Generally, KGC can be regarded as structure prediction tasks, where a model is trained to approximate a target function $F(x) \rightarrow y$, where $x \in \mathcal{X}$ denotes the input data and $y \in \mathcal{Y}$ denotes the output structure sequence. 
+For instance, given a sentence, *"Steve Jobs and Steve Wozniak co-founded Apple in 1977.}"*: 
+
+- Named Entity Recognition aims to identify the types of entities, \eg, *‘Steve Job'*, *‘Steve Wozniak'* $\Rightarrow$ *PERSON*, *‘Apple'* $\Rightarrow$ *ORG*; 
+
+- Relation Extraction aims to identify the relationship of the given entity pair $\langle$*Steve Job*, *Apple*$\rangle$ as *founder*;
+
+- Event Extraction aims to identify the event type as *Business Start-Org* where *‘co-founded'* triggers the event and (*Steve Jobs*, *Steve Wozniak*) are participants in the event as *AGENT* and *Apple* as *ORG* respectively. 
+
+- Entity Linking aims to link the mention *Steve Job* to *Steven Jobs (Q19837)* on Wikidata, and *Apple* to *Apple (Q312)* as well.
+
+- Knowledge Graph Completion aims to complete incomplete triples $\langle$*Steve Job*, *create*,  *?*$\rangle$ for blank entities *Apple*, *NeXT Inc.* and *Pixar*.
+
+
 
 ## 🏳‍🌈 A Taxonomy of Current Methods