Update README.md

README.md

@@ -11,15 +11,19 @@ tags:
 - emotion-classification
 - african-languages
 - low-resource-nlp
-pretty_name: Wazobia Labs Nigerian Pidgin Evaluation Set
-version: 0.1.0-alpha
+- health-nlp
+- cultural-annotation
+pretty_name: Wazobia Labs Nigerian Pidgin Gold-Standard Evaluation Set
+version: 0.3.0
 ---
 
-# Wazobia Labs — Nigerian Pidgin Evaluation Set
+# Wazobia Labs — Nigerian Pidgin Gold-Standard Evaluation Set
 
-**Status:** In development — target release Q3 2026
+**Version:** v0.3 — May 2026
+**Entries:** 253 dual-verified gold-standard entries
 **Builder:** [Wazobia Labs](https://huggingface.co/WAZOBIALABS)
-**License:** CC-BY-4.0
+**License:** CC-BY-4.0 — commercial use permitted with attribution
+**Contact:** wazobialabs@gmail.com
 
 ---
 
@@ -27,86 +31,171 @@ version: 0.1.0-alpha
 
 Every AI lab building for Nigerian Pidgin has the same unsolved problem: **they cannot evaluate whether their model actually works.**
 
-There is no gold-standard benchmark. No culturally verified test set. No sarcasm corpus. No benchmark that captures the difference between *forming* and *contempt*, between *hustle_fatigue* and *hustle_energy*, between a sincere compliment and its sarcastic twin.
+No gold-standard benchmark exists. No culturally verified test set. No sarcasm corpus that captures Nigerian deadpan. No benchmark that distinguishes *forming* from *contempt*, *hustle_fatigue* from *hustle_energy*, a sincere compliment from its sarcastic twin delivered in the exact same words with the exact same flat tone.
 
 This evaluation set solves that.
 
 ---
 
-## What Will Be In This Dataset
+## Dataset Summary
 
-The Nigerian Pidgin Evaluation Set is a separate gold-standard corpus drawn from and extending the main [WAZOBIALABS/nigerian-pidgin-voice-text](https://huggingface.co/datasets/WAZOBIALABS/nigerian-pidgin-voice-text) dataset.
+| Specification | Current (v0.3) |
+|---|---|
+| Total entries | 253 gold-standard entries |
+| Emotion categories | 16 — all represented at minimum 15 entries |
+| Sarcasm pairs | 28 complete pairs (sincere + sarcastic twin) |
+| Health domain entries | 40 entries |
+| Female speaker representation | ~45% |
+| Inter-annotator agreement | In progress — preliminary Kappa above 0.70 |
+| Built from | Wazobia Labs Nigerian Pidgin Dataset v0.8 (550 entries) |
+| License | CC-BY-4.0 |
 
-### Target Specifications
+---
 
-| Specification | Target |
-|---|---|
-| Total entries | 200 gold-standard entries |
-| Emotion categories | Minimum 20 entries per category across all 13 original categories |
-| Sarcasm pairs | 40 complete pairs (sincere + sarcastic twin) |
-| Female speaker representation | Minimum 50% |
-| Health domain | Minimum 20 entries |
-| Inter-annotator agreement | Verified by second native speaker annotator |
-| Annotation quality | Every entry reviewed, not sampled |
+## The 16-Category Taxonomy
+
+This evaluation set uses the Wazobia Labs Nigerian Pidgin emotion taxonomy — 16 categories, four of which have no equivalent in any existing NLP framework:
+
+| Category | Type | Definition |
+|---|---|---|
+| **forming** | Nigerian-specific ★ | Deliberately performing emotional indifference as social armour — acting unbothered on purpose. A mask worn in public. AI reads this as neutral and misses everything. |
+| **hustle_fatigue** | Nigerian-specific ★ | The specific exhaustion of sustained economic grinding where stopping is not an option. Not burnout — the kind where you cannot afford to stop. |
+| **hustle_energy** | Nigerian-specific ★ | Fired-up grind motivation. Defiant optimism about economic achievement. Often includes the Lagos "before 30" cultural timeline urgency. |
+| **market_energy** | Nigerian-specific ★ | The sharp, alert, competitive transactional register of Lagos commerce. Not aggression — a specific deal-making emotional state. |
+| anger | Standard | Frustration, irritation, outrage |
+| betrayal | Standard | Feeling deceived or disrespected by someone trusted |
+| celebration | Standard | Communal wins, hype, collective joy |
+| contempt | Standard | Cold downward dismissal — icy, not hot like anger |
+| craving | Standard | Intense desire for something not yet present |
+| joy | Standard | Genuine happiness, excitement, delight |
+| neutral | Standard | No specific emotion detectable |
+| prayer_gratitude | Cultural | Spiritual thankfulness — the Nigerian testimony register |
+| pride | Standard | Confidence, swagger, self-assurance |
+| sarcasm | Critical | Meaning inversion through deadpan delivery — prosodically identical to sincere speech |
+| shock | Standard | Surprise mixed with disbelief |
+| suspicion | Standard | Wariness, awareness of attempted manipulation |
+
+---
+
+## What Makes This Gold-Standard
+
+### Sarcasm Pairs — The Most Dangerous Gap in Nigerian Pidgin NLP
+
+Nigerian sarcasm is delivered deadpan — prosodically identical to sincere speech. The same words, the same flat tone, the complete opposite meaning.
+
+"You don try well well" can be the warmest praise or the coldest insult. A model cannot distinguish them without cultural context. This evaluation set contains 28 complete sarcasm pairs: the same phrase annotated twice, once sincere and once sarcastic, with annotator notes documenting the contextual conditions that determine which reading applies.
 
-### What Makes This Gold-Standard
+Any model that scores well on this evaluation set has learned to handle Nigerian sarcasm. Any model that does not has a serious deployment risk.
 
-**Sarcasm pairs with sincere twins.** The exact same Pidgin phrase annotated twice — once sincere, once sarcastic. AI models must distinguish them using context and cultural register, not just vocabulary.
+### Health Domain Coverage
 
-**Nigerian emotion taxonomy.** Not positive/negative/neutral. The full 13-category taxonomy: *forming*, *hustle_fatigue*, *market_energy*, *prayer_gratitude*, *betrayal*, *craving*, and more — categories that cannot be built without lived Nigerian cultural knowledge.
+40 health domain entries capture how Nigerian patients actually communicate about their health — not how they communicate in clinical settings or translated health literature.
 
-**Tonal disambiguation entries.** Same phrase, different context, different meaning. *"E don do"* consoling someone crying vs commanding someone to stop fighting vs cutting off excessive talking. Your model must handle all three.
+"E don do, I just dey manage" — standard models read neutral. It means a patient has given up trying to get better and is merely surviving. That is a clinical signal that requires intervention. This evaluation set tests whether your model catches it.
 
-**Female voice representation.** Minimum 50% female-voiced entries — a hard architectural constraint, not a recommendation.
+Health domain entries cover: maternal health, chronic illness management, medication compliance, patient-provider communication, mental health expression, and acute symptom reporting.
 
-**Health domain coverage.** Maternal health, menstrual health, mental health, caregiving — registers completely absent from formal NLP corpora.
+### Cultural Annotation Methodology
+
+Every entry in this evaluation set was annotated by a native speaker with lived fluency across three Nigerian Pidgin registers: Warri Pidgin (the original creole form), Eastern Nigerian Pidgin, and Lagos Pidgin. Cultural authority — not institutional backing — is the methodological foundation.
+
+The annotator is an Igbo woman born in Aba, raised in Warri, educated in Owerri, living in Lagos. This trajectory is the methodology.
 
 ---
 
-## Why Evaluation Infrastructure Matters
+## Category Coverage
 
-When Meta, Google, Microsoft, and African AI labs build Nigerian Pidgin models, they face a fundamental problem: **what does "works" mean?**
+All 16 emotion categories are represented at minimum 15 entries:
 
-WAXAL and similar initiatives have built ASR corpora. They can transcribe. But can they understand?
+| Category | Entries |
+|---|---|
+| anger | 15 |
+| betrayal | 15 |
+| celebration | 15 |
+| contempt | 15 |
+| craving | 15 |
+| forming | 15 |
+| hustle_energy | 15 |
+| hustle_fatigue | 15 |
+| joy | 15 |
+| market_energy | 15 |
+| neutral | 15 |
+| prayer_gratitude | 15 |
+| pride | 15 |
+| sarcasm | 28 |
+| shock | 15 |
+| suspicion | 15 |
+| **Total** | **253** |
 
-Can they tell that *"You come early today oh"* is a sincere compliment when said to someone who arrived unexpectedly on time — and a devastating sarcastic insult when said to someone two hours late?
+---
 
-Can they tell that *"I dey mind my business"* is contempt, not neutrality?
+## Data Fields
 
-Can they score *hustle_fatigue* vs *hustle_energy* — two speakers both talking about the grind, one depleted and one fired up?
+Each entry contains 15 fields:
 
-Without an evaluation set that tests these distinctions, there is no way to know. **Wazobia Labs builds the evaluation set. You cannot skip the evaluation.**
+| Field | Description |
+|---|---|
+| entry_id | Unique identifier — format WZ-T-XXXX |
+| pidgin_text | The Nigerian Pidgin text |
+| english_gloss | Plain English meaning |
+| sentiment | positive / negative / neutral |
+| emotion_category | Primary emotion from 16-category taxonomy |
+| emotion_secondary | Secondary emotion where present |
+| register | casual / street / proverbial |
+| sarcasm_flag | yes / no |
+| prosody_match | matched / contradicts / neutral |
+| annotator_notes | Cultural context and annotation rationale |
+| topic_domain | health / money / work / social / faith / relationship / conflict / motivation / emotion / food / greeting / life |
+| speaker_gender | female / neutral |
+| intensity | 1–5 scale |
+| source_type | original / overheard / social_media / adapted |
+| date_added | ISO date |
 
 ---
 
-## Pricing and Access
+## Why Evaluation Infrastructure Matters
 
-The evaluation set will be released under CC-BY-4.0 with a standard tier for academic and research use.
+When Meta, Google, Microsoft, and African AI labs build Nigerian Pidgin models, they face a fundamental problem: **what does "works" mean?**
 
-Enterprise licensing for production deployment and model benchmarking will be available separately with support, update guarantees, and documentation.
+Existing corpora — the BBC Pidgin corpus, WAXAL ASR data — can transcribe. But can they understand?
 
-For early access and enterprise licensing enquiries: **wazobialabs@gmail.com**
+Can they tell that "You come early today oh" is sincere praise when said to someone who arrived unexpectedly on time — and devastating sarcasm when said to someone two hours late?
 
----
+Can they score *hustle_fatigue* versus *hustle_energy* — two speakers both talking about the grind, one depleted and one fired up?
 
-## Timeline
+Can they read "E don do, I just dey manage" as the clinical resignation it is rather than neutral filler?
 
-| Milestone | Target |
-|---|---|
-| Alpha structure established | May 2026 ✅ |
-| 100 gold-standard entries | June 2026 |
-| Inter-annotator review complete | July 2026 |
-| 200 gold-standard entries | August 2026 |
-| Public release v1.0 | Q3 2026 |
+Without this evaluation set, there is no way to know. **Wazobia Labs builds the evaluation infrastructure. You cannot skip the evaluation.**
 
 ---
 
 ## Foundation Dataset
 
-This evaluation set is built on and extends:
+This evaluation set is drawn from and verified against:
 
 **[WAZOBIALABS/nigerian-pidgin-voice-text](https://huggingface.co/datasets/WAZOBIALABS/nigerian-pidgin-voice-text)**
-v0.6 — 480 entries — 16 emotion categories — CC-BY-4.0
+v0.8 — 550 entries — 16 emotion categories — CC-BY-4.0
+
+---
+
+## Version History
+
+| Version | Entries | Date | Notes |
+|---|---|---|---|
+| v0.1 | ~100 | April 2026 | Initial eval set structure |
+| v0.2 | 230 | May 2026 | Expanded to 16 categories |
+| v0.3 | 253 | May 2026 | Built from corrected v0.8 main dataset — all categories at 15+ entries, 40 health entries |
+
+---
+
+## Roadmap
+
+| Milestone | Target |
+|---|---|
+| Inter-annotator agreement published | June 2026 |
+| 300+ entries | July 2026 |
+| Voice-matched evaluation entries | Month 4 |
+| v1.0 public release | Q3 2026 |
 
 ---
 
@@ -114,25 +203,36 @@ v0.6 — 480 entries — 16 emotion categories — CC-BY-4.0
 
 ```bibtex
 @dataset{wazobia_labs_pidgin_eval_2026,
-  author    = {Okoye, Stephanie},
-  title     = {Wazobia Labs Nigerian Pidgin Evaluation Set},
+  author    = {Okoye, Stephanie Nkemjika},
+  title     = {Wazobia Labs Nigerian Pidgin Gold-Standard Evaluation Set},
   year      = {2026},
-  version   = {0.1.0-alpha},
+  version   = {0.3.0},
   publisher = {Hugging Face},
   url       = {https://huggingface.co/datasets/WAZOBIALABS/nigerian-pidgin-eval},
   license   = {CC-BY-4.0},
-  note      = {In development — target release Q3 2026}
+  note      = {First gold-standard evaluation benchmark for Nigerian Pidgin emotion classification}
 }
 ```
 
 ---
 
+## Licensing and Access
+
+Published under **CC-BY-4.0** — free to use for research, academic, and commercial purposes with attribution.
+
+Enterprise licensing with support, update guarantees, and integration documentation available separately.
+
+**Contact:** wazobialabs@gmail.com
+
+---
+
 ## About Wazobia Labs
 
-Wazobia Labs builds African language AI infrastructure that doesn't exist but should. We identify the specific, high-value gaps in African language data that existing datasets leave open — then build exactly those gaps with commercial licensing, production-grade quality, and the cultural specificity that real AI products need.
+Wazobia Labs builds African language AI infrastructure that does not exist but should. We identify the specific, high-value gaps in African language data that existing datasets leave open — then build exactly those gaps with commercial licensing, production-grade quality, and the cultural specificity that real AI products need.
+
+**Not another Twitter scrape. Not another scripted studio recording. We build what they deliberately left out.**
 
+**HuggingFace:** [WAZOBIALABS](https://huggingface.co/WAZOBIALABS)
 **Contact:** wazobialabs@gmail.com
-**Hugging Face:** [WAZOBIALABS](https://huggingface.co/WAZOBIALABS)
-**Founded:** Lagos, Nigeria — 2025
+**Founded:** Lagos, Nigeria — 2026
 
-*Wa. Zo. Bia. The evaluation is coming.*