docs: add legend tables to the two README examples
Each example now shows the shareable `legend` as a table (Abbreviation → meaning), marking 🆕 the abbreviations the model coined for attributes absent from the base prompt (ASSUR_ID, PERMIS, PASSPORT, RCC, BIO_ID, SANG, DOSSIER…). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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README.md
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README.md
@@ -269,7 +269,21 @@ its own abbreviations** for attributes not in the base prompt (passport, permit,
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> Note de dossier complète : le patient mineur [PER_1.PRENOM:U] [PER_1.NOM:U] (né le [PER_1.DATE_NAISSANCE:2013], groupe sanguin B+, numéro d'assuré maladie [PER_1.ASSUR_ID:U], allergique aux arachides) … Ses parents, [PER_2.PRENOM:F] [PER_2.NOM:F] (mère, permis de séjour [PER_2.PERMIS:C], [PER_2.TELEPHONE:U]) et [PER_3.PRENOM:M] [PER_3.NOM:M] (père, passeport italien [PER_3.PASSPORT:U]), cosignent … Le Dr [PER_4.PRENOM:F] [PER_4.NOM:F] (n° RCC [PER_4.RCC:U]) a ouvert le dossier médical DM-2025-0417 … l'agent [PER_5.PRENOM:M] [PER_5.NOM:M] de la caisse [ORG_1.NOM:Assurance] … [PER_1.PRENOM:U] utilise l'identifiant biométrique [PER_1.BIO_ID:U].
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> Note de dossier complète : le patient mineur [PER_1.PRENOM:U] [PER_1.NOM:U] (né le [PER_1.DATE_NAISSANCE:2013], groupe sanguin B+, numéro d'assuré maladie [PER_1.ASSUR_ID:U], allergique aux arachides) … Ses parents, [PER_2.PRENOM:F] [PER_2.NOM:F] (mère, permis de séjour [PER_2.PERMIS:C], [PER_2.TELEPHONE:U]) et [PER_3.PRENOM:M] [PER_3.NOM:M] (père, passeport italien [PER_3.PASSPORT:U]), cosignent … Le Dr [PER_4.PRENOM:F] [PER_4.NOM:F] (n° RCC [PER_4.RCC:U]) a ouvert le dossier médical DM-2025-0417 … l'agent [PER_5.PRENOM:M] [PER_5.NOM:M] de la caisse [ORG_1.NOM:Assurance] … [PER_1.PRENOM:U] utilise l'identifiant biométrique [PER_1.BIO_ID:U].
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Attributes **coined by the model** (not in the prompt): `ASSUR_ID`, `PERMIS`, `PASSPORT`, `RCC`, `BIO_ID`.
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**`legend` 🏷️ (shareable with the downstream model; 🆕 = coined by the model, not in the base prompt):**
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| Abbreviation | Meaning | |
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| ---------------- | ------------------------- | --- |
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| `PER` | Personne | |
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| `PRENOM` / `NOM` | Prénom / Nom de famille | |
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| `M` / `F` / `U` | Masculin / Féminin / n.d. | |
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| `DATE_NAISSANCE` | Date de naissance | |
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| `TELEPHONE` | Numéro de téléphone | |
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| `ORG` | Organisation | |
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| `ASSUR_ID` | Numéro d'assuré | 🆕 |
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| `PERMIS` / `C` | Permis de séjour / type C | 🆕 |
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| `PASSPORT` | Numéro de passeport | 🆕 |
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| `RCC` | Numéro RCC (médecin) | 🆕 |
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| `BIO_ID` | Identifiant biométrique | 🆕 |
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### A multi-turn conversation — 4 people; blood group recalled turn 1 → turn 6
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### A multi-turn conversation — 4 people; blood group recalled turn 1 → turn 6
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@@ -285,6 +299,22 @@ Noah stays `PER_1` across all six turns, and **his blood group `[PER_1.SANG:B+]`
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turn 6** — long-range coreference holds. (The father shares the surname, so `[PER_1.NOM:U]` is reused for
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turn 6** — long-range coreference holds. (The father shares the surname, so `[PER_1.NOM:U]` is reused for
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it — the same value maps to the same token.)
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it — the same value maps to the same token.)
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**`legend` 🏷️ (cumulative across the conversation; 🆕 = coined by the model):**
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| Abbreviation | Meaning | |
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| ---------------- | ------------------------------ | --- |
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| `PER` | Personne | |
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| `PRENOM` / `NOM` | Prénom / Nom de famille | |
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| `M` / `F` / `U` | Masculin / Féminin / inconnu | |
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| `DATE_NAISSANCE` | Date de naissance | |
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| `AVS` | Numéro d'assuré | |
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| `SANG` | Groupe sanguin | 🆕 |
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| `PERMIS` / `C` | Permis de séjour / établissem. | 🆕 |
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| `PASSPORT` | Numéro de passeport | 🆕 |
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| `SUI` / `ITA` | Suisse / Italie | 🆕 |
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| `TITRE` / `MED` | Titre professionnel / médical | 🆕 |
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| `DOSSIER` | Numéro de dossier | 🆕 |
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**[→ See all 10 examples, with full `mapping` and `legend` tables](./examples/RESULTS.md)**
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**[→ See all 10 examples, with full `mapping` and `legend` tables](./examples/RESULTS.md)**
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## How this helps with the nLPD
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## How this helps with the nLPD
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