Mining elements of carbonatite-type rare earth deposits based on knowledge map

doi:10.13745/j.esf.sf.2025.3.31

Abstract

Abstract:

Rare earth elements (REEs) are critical for modern high-tech industries, yet the metallogenic characteristics and mechanisms of carbonatite-hosted REE deposits remain poorly understood, significantly hindering exploration breakthroughs. With the advent of the geoscience big data era, knowledge graph technology has emerged as a key tool for mineral resource prediction. This study integrates natural language processing (NLP) techniques and knowledge graph construction methods to systematically investigate the metallogenic characteristics and mechanisms of carbonatite-hosted REE deposits. We collected literature pertaining to the Bayan Obo deposit and the Mianning-Dechang metallogenic belt. Using the BERT-BiLSTM-CRF model for entity recognition and the BERT model for relationship extraction, we constructed a domain-specific knowledge graph. Results indicate that minerals, rocks, and elements are critical nodes influencing mineralization. Fluorite exhibits high consistency across regional knowledge graphs, highlighting its potential as a prospecting indicator mineral. Europium and cerium, due to their redox-sensitive anomalies, serve as important indicators for REE exploration. Calcite and bastnaesite also demonstrate indicative potential. The knowledge graph reveals that Bayan Obo exhibits stronger associations with carbonatites, while the Mianning-Dechang belt is more closely linked to alkaline rocks. Hierarchical clustering further demonstrates significant correlations among similar nodes, providing key insights into the metallogenic environment and critical elements. This study offers a novel perspective and methodology for understanding metallogenic mechanisms and provides robust scientific support for the exploration and evaluation of REE deposits.

Key words: knowledge graph, carbonatite, rare earth deposits, Bayan Obo, Mianning-Dechang

CLC Number:

FENG Tingting, CAI Shirou, ZHANG Zhenjie. Mining elements of carbonatite-type rare earth deposits based on knowledge map[J]. Earth Science Frontiers, 2025, 32(4): 262-279.

Figures/Tables 19

References 78

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属性	实体
矿物	barite、galena、pyrite、aegirine、biotite
岩石	carbonatite、gabbro、basalt、pegmatite、syenite
元素	REE、Ca、Mg、Eu、Sm
年代	Paleogene、Neoproterozoic、Paleozoic、Jurassic、Permian
化学	NaCl、SO₄、SiO₂、TiO₂、Rb/Sr、²⁰⁸Pb/²⁰⁴Pb
矿床	Maoniuping、Dalucao、Lizhuang、Weishan、Bayan Obo
构造	mantle、dike、Mianning-Dechang、vein、Craton、fault

属性	实体
矿物	barite、galena、pyrite、aegirine、biotite
岩石	carbonatite、gabbro、basalt、pegmatite、syenite
元素	REE、Ca、Mg、Eu、Sm
年代	Paleogene、Neoproterozoic、Paleozoic、Jurassic、Permian
化学	NaCl、SO₄、SiO₂、TiO₂、Rb/Sr、²⁰⁸Pb/²⁰⁴Pb
矿床	Maoniuping、Dalucao、Lizhuang、Weishan、Bayan Obo
构造	mantle、dike、Mianning-Dechang、vein、Craton、fault

无用实体	多余符号输出	方法名称	缩写/全称
deep open	diopside (40	ICP-MS	REE/rare earth element
deposit	dolerite,	LA-ICP-MS	LREE/light REE
detail	dolomite <	MC-ICP-MS	MD/Mianning-Dechang
discrete	dolomite δ¹⁸O	EPMA	MNP/Maoniuping

无用实体	多余符号输出	方法名称	缩写/全称
deep open	diopside (40	ICP-MS	REE/rare earth element
deposit	dolerite,	LA-ICP-MS	LREE/light REE
detail	dolomite <	MC-ICP-MS	MD/Mianning-Dechang
discrete	dolomite δ¹⁸O	EPMA	MNP/Maoniuping

节点名称	白云鄂博
图谱名称	calcite			carbonatite			Sr
中间节点数	权重	路径	用时	权重	路径	用时	权重	路径	用时
0	0.192 9	2	<1 s	0.278 2	2	<1 s	0.12	2	<1 s
1	0.338 6	318	<1 s	0.463 3	679	<1 s	0.268 8	267	<1 s
2	0.454 6	18 511	<1 s	0.593 7	26 129	2 s	0.385 8	16 726	<1 s
3	0.540 9	1 328 379	57 s	0.688 6	1 855 502	71 s	0.474 6	1 169 663	49 s
4	0.605 3	86 737 483	3 709 s	0.757 6	118 441 560	4 668 s	0.541 7	77 172 134	3 820 s
5	—	—	—	—	—	—	—	—	—
节点名称	冕宁—德昌
图谱名称	calcite			carbonatite			Sr
中间节点数	权重	路径	用时	权重	路径	用时	权重	路径	用时
0	0.156 9	2	<1 s	0.323 9	2	<1 s	0.132 4	2	<1 s
1	0.292 5	150	<1 s	0.492 4	317	<1 s	0.277 5	167	<1 s
2	0.398 9	4 395	<1 s	0.609 1	7 143	<1 s	0.384 9	4 887	<1 s
3	0.480 4	146 158	5 s	0.693	223 796	7 s	0.464 5	161 150	5 s
4	0.540 8	4 491 471	171 s	0.753 2	6 426 434	216 s	0.523 5	4 900 533	181 s
5	0.584 9	135 771 508	5 188 s	0.796 1	182 967 342	6 537 s	0.567 2	146 940 976	5 549 s