DianShi-RxnDB: A Large-Scale, Fine-Grained Organic Reaction Data Platform Built via a Fully Automated Pipeline for Researchers and AI Agents

Yubin Wang; Xingjian Wei; Jiang Wu; Yinfan Wang; Boyu Zhu; Lin Zhang; Jianing Yu; Huazheng Zeng

cs.CLSep 6, 2026

DianShi-RxnDB: A Large-Scale, Fine-Grained Organic Reaction Data Platform Built via a Fully Automated Pipeline for Researchers and AI Agents

Authors: Yubin Wang, Xingjian Wei, Jiang Wu, Yinfan Wang, Boyu Zhu, Lin Zhang, Jianing Yu, Huazheng Zeng,

Organizations: Shanghai Artificial Intelligence Laboratory

Abstract

High-quality structured organic reaction data are essential for developing artificial intelligence for chemistry (AI4Chem), yet much of this knowledge remains dispersed across patent text, images, and reaction schemes. We present DianShi-RxnDB, a large-scale, fine-grained organic reaction data platform built via a fully automated extraction and normalization pipeline integrating patent text, images, and reaction schemes. Its corpus covers organic synthesis patents from the USPTO and EPO published between 1976 and 2025, yielding approximately 24 million reaction instances, of which approximately 14.8 million (61.7%) pass automated qualification checks. Each instance represents a specific single-step experiment recording participants, roles, quantities, temperatures, reaction times, yields, experimental procedures, and provenance links to source patents. In a manual evaluation of 1,300 sampled qualified instances, the micro-averaged field-level accuracy was 92.95%. A matched comparison with Pistachio further indicated advantages in deduplicated record counts, representation granularity, and field-level exact agreement. The platform provides a Web research workbench for searching, filtering, comparing, and source-verifying records, and a Model Context Protocol (MCP) service offering AI agents composable structured retrieval tools. DianShi-RxnDB is available at https://dianshi.opendatalab.org.cn/ .

Figures & tables

Figure 1: System architecture and data-flow overview of DianShi-RxnDB. Through a fully automated information-extraction and normalization pipeline, DianShi-RxnDB transforms approximately 1.58 million patent documents from the USPTO and EPO, primarily covering 1976–2025, into approximately 24 million fine-grained, provenance-linked Reaction Instances , of which approximately 14.8 million (61.7%) pass automated qualification assessment. The instance-level data include reaction participants, experimental conditions, and procedures, with structured relationships among Substances , Reaction Instances , Reaction Groups , and References . These relationships support the organization and comparison of related single-step reaction records and provide a path back to source patents for verification. On this shared data foundation, the Web research workbench provides interactive search, comparison, and source verification for researchers, while the MCP service provides AI agents with structured, composable, multi-step retrieval capabilities.

Resource name	Reported scale	Literature coverage	Reaction and experimental fields	Provenance location	Access mode
USPTO-Lowe [ 21 , 27 ]	$\sim$ 3.75 M	1976–2016	$\mathcal{R}\!\cdot\!\mathcal{Q}\!\cdot\!\mathcal{C}\!\cdot\!\mathcal{P}\!\cdot\!\mathcal{Y}$	Document	Public download
CJHIF [ 19 , 18 ]	$\sim$ 3.22 M	Not specified	$\mathcal{R}\!\cdot\!\mathcal{Y}$	Not localized	Public repository
USPTO-LLM [ 37 , 36 , 13 ]	$\sim$ 247,000	1976–2016	$\mathcal{R}\!\cdot\!\mathcal{C}\!\cdot\!\mathcal{S}$	Document	Public download
Pistachio [ 26 , 23 , 24 ]	$\sim$ 21 M	1971–present	$\mathcal{R}\!\cdot\!\mathcal{Q}\!\cdot\!\mathcal{C}\!\cdot\!\mathcal{P}\!\cdot\!\mathcal{Y}$	Paragraph	Paid Web access
Reaxys [ 9 , 10 ]	$\sim$ 73 M	1771–present	$\mathcal{R}\!\cdot\!\mathcal{C}\!\cdot\!\mathcal{Y}$	Document	Paid Web; MCP/API license
CAS Reactions [ 1 , 2 ]	$\sim$ 150 M	1840–present	$\mathcal{R}\!\cdot\!\mathcal{Q}\!\cdot\!\mathcal{C}\!\cdot\!\mathcal{S}\!\cdot\!\mathcal{Y}$	Document	Paid Web access

Table 1: Representative organic reaction data resources and their system characteristics. The table compares the reported scale, original-literature coverage, reaction and experimental fields, provenance location, and access mode of each resource. Here, “reaction and experimental fields” refers to information captured at the reaction-record or reaction-instance level, including participant roles, quantities or scale, conditions, multistage support, structured procedures, yield, and other outcomes. The symbols indicate fields or capabilities documented in the cited materials and do not imply that every record contains every field. For the field notation,

\mathcal{R}

denotes reaction participants and roles,

\mathcal{Q}

quantities or scale,

\mathcal{C}

reaction conditions,

\mathcal{S}

support for multistage reactions,

\mathcal{P}

a structured procedure mapped from the literature to predefined operations and parameters,

\mathcal{Y}

yield, and

\mathcal{O}

outcomes other than yield. For provenance location, “document” indicates an association with the original literature without confirmed paragraph-level localization, whereas “paragraph” indicates a paragraph-level location.

Processing stage	Input records	Removed records	Retained records
Source USPTO and EPO patent records	—	—	20,256,438
IPC-based filtering for organic chemistry relevance	20,256,438	17,743,513	2,512,925
Within-source consolidation and deduplication	2,512,925	544,695	1,968,230
Cross-source deduplication between USPTO and EPO	1,968,230	210,475	1,757,755
Removal of records without usable full text	1,757,755	176,816	1,580,939

Table 2: Processing stages from source patent records to the reaction-extraction corpus.

Information category	Principal content
Reaction representation	Reactant–product structural representation; Reaction SMILES
Participants and roles	Reactant, Product, Reagent, Catalyst, and Solvent
Instance-level amounts	Available information such as quantities, equivalents, and product amounts
Reaction conditions	Available conditions such as temperature and time
Outcome information	Experimental results such as yield
Experimental process	Available experimental procedures and workup descriptions

Table 3: Principal information organized in a Reaction Instance .

Figure 2: DianShi-RxnDB transforms patent documents into provenance-linked Reaction Instances through a fully automated information-extraction and normalization pipeline. The pipeline parses patent text, images, and reaction schemes and, without manual extraction and curation of individual records, identifies organic synthesis experiments and organizes reaction participants, experimental conditions, yields, and experimental procedures into structured Reaction Instances ; chemical information in images and reaction schemes is primarily parsed by MinerU.Chem. Each instance retains a link to the relevant source-patent location to support source-text verification. Automated qualification then assigns each generated record a “qualified” or “not passed” status. Both categories are retained in the database with their extracted information and provenance links.

Figure 3: Conceptual relationships among Reaction Instances , Reaction Groups , and Reaction Templates . (A) A Reaction Instance represents a specific reported single-step reaction and independently retains its reaction conditions, yield, experimental procedure, and source information. A Reaction Group organizes multiple Reaction Instances using the same normalized reactant–product grouping key, without merging their experimental information. (B) A Reaction Template represents a local structural transformation pattern shared by different complete reaction instances, so instances with different specific reactant–product combinations may be associated with the same template. The local transformation shown in the figure is a simplified pattern for illustration and is not the SMARTS expression actually stored by the database.

Database object	Count	Counting convention
Source patent documents ( References )	608,309	USPTO or EPO patent documents linked to at least one retained Reaction Instance
Substances	6,261,797	Substance records organized by chemical identity in the database
Reaction Instances	23,999,236	Specific reported experiments extracted from patents and retained in the database
Reaction Groups	6,580,963	Groups formed from normalized reactant–product identity combinations
LocalRetro Reaction Templates	1,190,000	Deduplicated template collection generated using LocalRetro
RDChiral Reaction Templates	1,860,000	Deduplicated template collection generated using RDChiral

Table 4: Scale of core DianShi-RxnDB data objects.

Automated qualification status	Count	Share of all Reaction Instances
Qualified instances	14,808,205	61.7%
Not qualified instances	9,191,031	38.3%
Total	23,999,236	100%

Table 5: Automated qualification status of Reaction Instances .

Field	Correct judgments	Evaluated records	Field-level accuracy
Yield	1,233	1,300	94.85%
Reactant	1,226	1,300	94.31%
Reagent	1,100	1,300	84.62%
Catalyst	1,265	1,300	97.31%
Solvent	1,218	1,300	93.69%
Micro-average across five fields	6,042	6,500	92.95%

Table 6: Manual quality-evaluation results for five reaction fields in qualified Reaction Instances .

Dataset	Raw records	Records retained after deduplication	Duplicates removed
DianShi-RxnDB	4,222	4,093	129
Pistachio, text + image	3,630	2,992	638

Table 7: Reaction-record counts before and after deduplication in the matched sample of 100 US patents.

Selected differentiating feature	DianShi-RxnDB	Inspected Pistachio record
Separate Reagent and Catalyst roles	Yes	No ; broad Agent
Stage-level reaction object	Yes	No
Dedicated workup field	Yes	No
Explicit validation diagnostics	Yes	No

Table 8: Selected differentiating representation features observed for the shared reaction Intermediate 4 in patent US10975080. “Yes” indicates an explicitly represented feature; “No” indicates that no corresponding standalone field or object was exposed in the inspected record. This is not an exhaustive field inventory.

Field	Pistachio	DianShi-RxnDB	Gap
Reactant	623/660 (94.39%)	643/660 (97.42%)	+3.03%
Reagent	555/660 (84.09%)	576/660 (87.27%)	+3.18%
Catalyst	553/660 (83.79%)	569/660 (86.21%)	+2.42%
Solvent	615/660 (93.18%)	629/660 (95.30%)	+2.12%
Product	604/660 (91.52%)	609/660 (92.27%)	+0.75%
Yield	535/660 (81.06%)	656/660 (99.39%)	+18.33%

Table 9: Field-level exact agreement against source-grounded references in 660 source-paragraph-matched reaction pairs.

Figure 4: Structured Reaction Instance and source-patent comparison in the Web research workbench. The left panel shows experimental content from the source patent, while the right panel shows structured reaction information for the corresponding Reaction Instance , including reaction structures, participants, amounts, and experimental conditions. For records with available source content and location information, users can locate and compare the relevant source-patent paragraph or text region in the same interface to verify experimental procedures, participant roles, experimental conditions, and yields.

Instance	Reagent / catalyst	Solvent	Temp.	Time	Yield	Source patent
A	Sulfuric acid	Not recorded	50 ∘ C	20 min	70%	US10407376B2 [ 6 ]
B	SOMS	Dichloromethane	40 ∘ C	Not rec.	97%	US20220008887A1 [ 32 ]
C	Sulfated zirconia	Not recorded	120 ∘ C	30 min	92–95%	US20090082592A1 [ 17 ]

Table 10: Representative patent reaction instances for the formation of aspirin from salicylic acid and acetic anhydride.

Figure 5: Web use case from an aspirin target structure to patent reaction precedents and source verification. (A) The user enters or draws the aspirin structure, matches the corresponding Substance , restricts its participant role to Product, and enters the related reaction instances. (B) Among the 84 Reaction Instances associated with aspirin as a Product, the user locates the target Reaction Group in which salicylic acid and acetic anhydride form aspirin. This group contains 53 Reaction Instances from 10 source patents, with each instance’s experimental conditions, yield, and source information retained separately for comparison. (C) The user opens the source patent associated with Instance A and verifies the catalyst sulfuric acid, temperature of 50 ∘ C, and time of 20 minutes in the structured record.

Figure 6: From a natural-language task to multi-step MCP retrieval and example source inspection. (A) The AI agent calls the DianShi MCP according to the natural-language task: it retrieves 11 candidate Reaction Groups by the aspirin product structure, then locates 1 target Reaction Group from the salicylic-acid–acetic-anhydride reactant combination. The group contains 53 Reaction Instances , of which 20 are returned by the condition query in this call. (B) Based on the MCP results returned in this call, the agent organizes the target Reaction Group and selected representative Reaction Instances with their experimental conditions, yields, and source information. (C) Using Instance B as an example, the agent uses the reaction and source information returned by MCP to locate the corresponding record in the Web research workbench and inspect the source patent for SOMS, dichloromethane, 40 ∘ C, and 97% as reported experimental information.

Object or term	Definition	Primary use
Reference	A source patent document represented as a database object	Connects patent metadata and source content with Reaction Instances
Substance	A substance record organized by chemical identity in the database	Supports name, identifier, and structure retrieval; links to related reactions
Reaction Instance	Specific single-step reaction record extracted from a patent and retained in the database	Stores participant roles, conditions, yield, procedure, and provenance
Reaction Group	Groups Reaction Instances with the same normalized reactant–product identity	Organizes instances for one normalized reactant–product combination
Reaction Template	Abstract reaction representation using SMARTS	Provides an abstract representation beyond a specific reactant–product combination
Reaction Participant	A participation relationship between a Substance and a Reaction Instance	Records a Substance role as Reactant, Product, Reagent, Solvent, or Catalyst

Table A1 : Core DianShi-RxnDB objects and terminology.

Field	Description	Example
Document name	Patent name or title	Therapeutic agent for Parkinson disease
Document type	Type of source document	PATENT
Document number	Patent identifier	US054849209-19960116
Authors or organization	Patent inventors or organization	Suzuki; Fumio; Shimada; Junichi; Koike; Nobuaki et al.

Table B1: Principal Reference fields.

Field or group	Description	Example ( DianShi-RxnDB Web record )
In-document number	Subheading at the provenance location of the reaction in the patent	Intermediate 68
Yield	Product yield	75%
SMILES	Simplified SMILES	[CH3:1][c:2]1[cH:3][c:4]2c:5[cH:15][c:16]1N+:17[O-]>>[CH3:1][c:2]1[cH:3][c:4]2c:5[cH:15][c:16]1[NH2:17]
Confidence	Confidence for the SMILES	86.80%
Condition: Temp.	Reaction temperature	RT
Condition: Time	Reaction time	18h

Table B2 : Principal Reaction Instance fields.

Field or group	Description	Example
Substance name	IUPAC name of the substance	8-(E)-3,4-Dimethoxystyryl-1,3-dipropyl-7-methylxanthine
Molecular formula	Molecular formula of the substance	C22H28N4O4
Molecular weight	Molecular weight of the substance	412.49
Canonical SMILES	Canonical SMILES of the substance	CCCn1c(=O)c2c(nc(/C=C/c3ccc(OC)c(OC)c3)n2C)n(CCC)c1=O
InChI	International Chemical Identifier	1S/C22H28N4O4/c1-6-12-25-20-19(21(27)26(13-7-2)22(25)28)24(3)18(23-20)11-9-15-8-10-16(29-4)17(14-15)30-5/h8-11,14H,6-7,12-13H2,1-5H3/b11-9+
Association statistics for 1,4-butanediol	Patent records containing the Substance	2,302

Table B3: Principal Substance fields and association statistics.

Operation	Definition
Add	Add a substance to the reactor
Centrifuge	Centrifuge the mixture to separate phases or collect solids
CollectLayer	Select aqueous or organic fraction(s)
Column	Execute column chromatography using adsorbent and eluent
Combine	Combine multiple batches, fractions, or extracts
Concentrate	Evaporate the solvent (e.g., using a rotary evaporator)

Table B4: Operational definitions for reaction-process details.

Raw JSON field	Text channel	Image channel
title	US07795244B2_0103	US07795244_C00043
data.paragraphText	In step 5, in a suitable reaction flask, sodium iodide (23.9 g, 159.45 mmol, 1.6 eq.) was dissolved in acetone (96 mL). 2-Ethoxy-isobutyric acid chloromethyl ester (18 g, 99.65 mmol, 1 eq.) was then added ...	Field absent
Deduplication result	Same reactant and product sets after removing atom-map numbers and sorting components	Same reactant and product sets after removing atom-map numbers and sorting components

Table D1 : Raw record identifiers, source text, and deduplication result for the text- and image-channel records of the same patent example in US07795244.

Field in this reaction	DianShi-RxnDB	Pistachio
Source pointer	Intermediate 4 ; source line 1306; full paragraph	US10975080B2_0290 ; paragraphText
Role labels	Reactant; Reagent; Solvent; Product	Reactant; broad Agent ; Solvent; Product
Catalyst field	Explicitly recorded and empty for this reaction	— No separate Catalyst field
Reaction stage	stage_1 groups substances, conditions, actions, and workup	— No stage-level object
Temperature	Stage field: 0 °C	Action parameter: Temperature = 0 °C
Time	Stage field: 2 h	Action parameter: Time = 2 h

Table D2 : Concrete field-level evidence for the shared reaction Intermediate 4 in patent US10975080.

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