diff --git a/README.md b/README.md
index d2a7675..1f49019 100644
--- a/README.md
+++ b/README.md
@@ -99,6 +99,12 @@ Furthermore, this repository might serve as a **cristallization point for a comm
             - OWL
             - OBOGraph JSON format
             - SSSOM
+- [LangChain](https://github.com/langchain-ai/langchain)'s GraphSparqlQAChain – A LangChain module for making RDF and OWL accessible via natural language
+    - docs: https://python.langchain.com/docs/use_cases/graph/graph_sparql_qa
+    - features:
+        - Generates SPARQL SELECT and UPDATE queries from natural language
+        - Runs the generated queries against local files, endpoints, or triple stores
+        - Returns natural language responses
 - [LinkML](https://github.com/linkml/linkml) – Linked Open Data Modeling Language
     - features:
         - A high level simple way of specifying data models, optionally enhanced with semantic annotations
@@ -111,12 +117,12 @@ Furthermore, this repository might serve as a **cristallization point for a comm
         - Verifying (non-trivial) logical consistency of a CLIF ontology
         - Proving theorems/lemmas, such as properties of concepts and relations or competency questions
         - GUI (alpha state)
-- [Morph-KGC](https://github.com/oeg-upm/morph-kgc) – Engine to create RDF and RDF-star knowledge graphs from heterogeneous sources with R2RML, RML and RML-str
+- [Morph-KGC](https://github.com/oeg-upm/morph-kgc) – System to create RDF and RDF-star knowledge graphs from heterogeneous sources with R2RML, RML and RML-star
   - docs: https://morph-kgc.readthedocs.io
   - features:
     - support for relational databases, tabular files (e.g. CSV, Excel, Parquet) and hierarchical files (XML and JSON)
-    - generates the RDF and RDF-star knowledge graphs by running through command line or as a library
-    - Integrates with RDFlib and Oxigraph to load the generated RDF directly to those libraries
+    - generates RDF and RDF-star knowledge graphs by running through the command line or as a library
+    - integrates with RDFlib and Oxigraph to load the generated RDF directly to those libraries
 - [nxontology](https://github.com/related-sciences/nxontology) – NetworkX-based library for representing ontologies
   - features:
     - load ontologies into a `networkx.DiGraph` or `MultiDiGraph` from `.obo`, `.json`, or `.owl` formats
@@ -161,6 +167,12 @@ Furthermore, this repository might serve as a **cristallization point for a comm
     - features:
         -supports several ontology languages and formats
     - docs: https://pronto.readthedocs.io/en/latest/api.html
+- [pycottas](https://github.com/arenas-guerrero-julian/pycottas) – Library for working with compressed COTTAS files
+  - docs: https://pycottas.readthedocs.io
+  - features:
+    - compress RDF files to COTTAS format
+    - evaluate triple patterns over compressed RDF
+    - integrates with RDFlib as a store backend to query COTTAS files with SPARQL
 - [pyfactxx](https://github.com/tilde-lab/pyfactxx) – Python bindings for FaCT++ OWL 2 C++ reasoner
     - features:
         - well-optimized reasoner for SROIQ(D) description logic, with additional improvements
@@ -168,6 +180,13 @@ Furthermore, this repository might serve as a **cristallization point for a comm
         - easy cross-platform installation
 - [PyFuseki](https://github.com/yubinCloud/pyfuseki) – Library that interact with Jena Fuseki (SPARQL server):
     - docs: https://yubincloud.github.io/pyfuseki/
+
+- [PyKEEN](https://github.com/pykeen/pykeen) (**Py**thon **K**nowl**E**dge **E**mbeddi**N**gs) – Python package to train and evaluate knowledge graph embedding models
+    - features:
+        - 44 Models
+        - 37 Datasets
+        - 5 Inductive Datasets
+        - support for multi-modal information
 - [PyLD](https://github.com/digitalbazaar/pyld) - A JSON-LD processor written in Python
     - conforms:
         - JSON-LD 1.1, W3C Candidate Recommendation, 2019-12-12 or newer
@@ -194,6 +213,8 @@ Furthermore, this repository might serve as a **cristallization point for a comm
     - resolution-based theorem provers for first-order logic
     - focus on good comprehensibility of the code
     - Literature: [Teaching Automated Theorem Proving by Example](https://link.springer.com/chapter/10.1007/978-3-030-51054-1_9)
+- [pystardog](https://github.com/stardog-union/pystardog)
+    - Python bindings for the [Stardog Knowledge Graph platform](https://www.stardog.com/)
 - [Quit Store](https://github.com/AKSW/QuitStore) – workspace for distributed collaborative Linked Data knowledge engineering ("Quads in Git")
     - features:
         - read and write RDF Datasets
@@ -228,6 +249,16 @@ by Natanael Arndt, Patrick Naumann, Norman Radtke, Michael Martin, and Edgard Ma
     - serving local RDF files using the command line interface
 - [serd](https://gitlab.com/drobilla/python-serd) – Python serd module, providing bindings for Serd, a lightweight C library for working with RDF data
   - docs:  https://drobilla.gitlab.io/python-serd/singlehtml/
+- [ sparqlfun](https://github.com/linkml/sparqlfun)
+    - LinkML based SPARQL template library and execution engine
+        - modularized core library of SPARQL templates
+        - Fully FAIR description of templates
+        - Rich expressive language for moedeling templates
+            - uses [LinkML](https://linkml.io/linkml/) as base language
+        - optional python bindings / [object model](https://github.com/linkml/sparqlfun/blob/main/sparqlfun/model.py) using LinkML
+        - supports both SELECT and CONSTRUCT
+        - optional export to TSV, JSON, YAML, RDF
+        - extensive [endpoint metadata](https://github.com/linkml/sparqlfun/tree/main/sparqlfun/config)
 - [SPARQL kernel](https://github.com/paulovn/sparql-kernel) for Jupyter
     - features:
         - sending queries to an SPARQL endpoint