Update CHANGELOG.md for Release (#43)

CHANGELOG.md

@@ -4,6 +4,17 @@ All notable changes to this project will be documented in this file.
 
 Instructions on how to update this Changelog are available in the `Updating the Changelog` section of the [`CONTRIBUTING.md`](./CONTRIBUTING.md).  This project follows [semantic versioning](https://semver.org/spec/v2.0.0.html).
 
+## [Pre-release v0.1.0-alpha]
+
+Initial pre-release of `PrivFp - Experiments` containing open-weights replacements for all components from original PoC
+
+#### Significant features
+- Open-weight model integration (e.g. Llama-family, GLiNER, etc.)
+- Configuration approach
+- Experiment 1.0
+- Documentation and Research Spikes (e.g. Standardisation)
+- Annotation investigations
+
 ## [Unreleased v0.0.1]
 
 Initial Repo release

docs/background/decision-log.md

@@ -15,6 +15,6 @@ Here we collect decisions made throughout the project, focused on tooling, techn
 | **04/06/24** | *Configuration approach integrated* :abacus: |
 | **29/07/24** | *Add newer Llama 3 model options* :llama::llama::llama: |
 | **02/08/24** | *Merge in exploration on annotation tooling as spike* :pencil: |
-| **28/08/24** | *Integrate pycanon for access to other privacy metrics* |
+| **28/08/24** | *Integrate pycanon for access to other privacy metrics* :8ball: |
 | **09/09/24** | *Add newer Llama 3.1 model options* :llama::llama::llama::point_right::llama: |
-| **16/09/24** | *Discussion of Experiment 1.0 included* |
+| **16/09/24** | *Discussion of Experiment 1.0 included* :construction_worker: |

docs/background/experiment-1point0.md

@@ -1,6 +1,6 @@
 # Experiment 1.0
 
-*This version of `Experiment 1.0` was run using the repo at commit [INSERT git SHA](), and looks to explore generic clinical notes containing four entities: `NHS Number`, `Person`, `Date of Birth`, and `Diagnosis`.  We also explore extracting further common entities which weren't explicitly injected.*
+*This version of `Experiment 1.0` was run using the repo at commit [`da9cc98`](https://github.com/nhsengland/privfp-experiments/commit/da9cc9877052cd66275315ce0f6bf7edf7dd360b), and looks to explore generic clinical notes containing four entities: `NHS Number`, `Person`, `Date of Birth`, and `Diagnosis`.  We also explore extracting further common entities which weren't explicitly injected.*
 
 Let's run an experiment with the Privacy Fingerprint (PrivFp) pipeline to understand each modular component, and explore some of the things we can do within each section.