Update README.md

README.md

@@ -229,6 +229,42 @@ The Farm Workforce Modernization Act of 2023, which could grant legal status to
 
 </details>
 
+### Named-entity recognition
+
+For named-entity recognition tasks you can use the following prompt template:
+
+```
+Analyse the following tokenized text and mark the tokens containing named entities.
+Use the following annotation guidelines with these tags for named entities:
+- ORG (Refers to named groups or organizations)
+- PER (Refers to individual people or named groups of people)
+- LOC (Refers to physical places or natural landmarks)
+- MISC (Refers to entities that don't fit into standard categories).
+Prepend B- to the first token of a given entity and I- to the remaining ones if they exist.
+If a token is not a named entity, label it as O.
+Input: {list of words in a sentence}
+Marked: 
+```
+
+<details>
+<summary>Show en example</summary>
+  
+```python
+text = """Analyse the following tokenized text and mark the tokens containing named entities.
+Use the following annotation guidelines with these tags for named entities: 
+- ORG (Refers to named groups or organizations)
+- PER (Refers to individual people or named groups of people)
+- LOC (Refers to physical places or natural landmarks)
+- MISC (Refers to entities that don't fit into standard categories).
+Prepend B- to the first token of a given entity and I- to the remaining ones if they exist.
+If a token is not a named entity, label it as O.
+Input: ['La', 'defensa', 'del', 'antiguo', 'responsable', 'de', 'la', 'RFEF', 'confirma', 'que', 'interpondrá', 'un', 'recurso.']
+Marked: """
+
+# [('La', 'O'), ('defensa', 'O'), ('del', 'O'), ('antiguo', 'O'), ('responsable', 'O'), ('de', 'O'), ('la', 'O'), ('RFEF', 'B-ORG'), ('confirma', 'O'), ('que', 'O'), ('interpondrá', 'O'), ('un', 'O'), ('recurso.', 'O')]
+```
+
+</details>
 
 ## Data