Input path: /home/debian/html/nutritwin/output_llm/66e695ff517ce/input.json Output path: /home/debian/html/nutritwin/output_llm/66e695ff517ce/output.json Input text: Ce matin j'ai mangé une tranche de jambon et une orange DB path: __deriveddata__/DerivedObjects/Data/KcalMeDB_fr.sl3 Picto path: __deriveddata__/DerivedObjects/Data/PictoMatcherNetNG_fr.json Sport grounding path: __deriveddata__/DerivedObjects/Data/DerivedSportMET.json ================================================================================================================================== Prompt from user: Ce matin j'ai mangé une tranche de jambon et une orange ================================================================================================================================== ==================================== Prompt ============================================= Identify in this list of intents: ["Identify food consumption or declaration", "Identify the user physical activity", "Answer a nutrition question", "Other intent"], the intents of the prompt: ###Ce matin j'ai mangé une tranche de jambon et une orange###. Format the result in JSON format: {intents: []}. ========================================================================================= ------------------------------ LLM Raw response ----------------------------- ```json { "intents": ["Identify food consumption or declaration"] } ``` ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ ```json { "intents": ["Identify food consumption or declaration"] } ``` ------------------------------------------------------ ------------------------ After simplification ------------------------ { "intents": ["Identify food consumption or declaration"]} ---------------------------------------------------------------------- ==================================== Prompt ============================================= Convert this natural language query : """Ce matin j'ai mangé une tranche de jambon et une orange""" into an array in JSON of consumed foods and beverages. Provide a solution without explanation. Use only the ontology described in this Turtle/RDF model: """ @prefix food: . @prefix rdfs: . @prefix xsd: . @prefix owl: . @prefix prov: . food: a owl:Ontology ; rdfs:comment "Definition of the food archetype"@en . food:name a owl:DatatypeProperty; rdfs:label "name"@en; rdfs:comment "Food or drink identifier, the name should not contain information related to quantity or container (like glass...). The cooking mode is not in the name. When the brand is very well-known (ex: Activia, Coca-Cola), the name is equal to the brand. Keep the same language"@en; rdfs:range xsd:string. food:quantity a owl:DatatypeProperty ; rdfs:label "quantity"@en; rdfs:comment "The quantity of food or drink that is or was consumed. Quantity examples in french: 'un quignon', 'un cornet', 'un verre', 'une tranche', 'une boule', 'un', 'deux', 'trois',... Keep the same language."@en; rdfs:range xsd:string. food:cookingMethod a owl:DatatypeProperty ; rdfs:label "cooking method"@en; rdfs:comment "The cooking method of food. Keep the same language"@en; rdfs:range xsd:string. food:type a owl:DatatypeProperty ; rdfs:label "type of food"@en; rdfs:comment "Identify the type of food."@en; rdfs:range xsd:string. food:food a food:type ; rdfs:label "food" . food:beverage a food:type ; rdfs:label "beverage" . food:timeOfTheDay a owl:DatatypeProperty ; rdfs:label "time of the day"@en; rdfs:comment "Time of the day when food or drink was consumed."@en; rdfs:range xsd:string. food:breakfast a food:timeOfTheDay ; rdfs:label "breakfast" . food:lunch a food:timeOfTheDay ; rdfs:label "lunch" . food:snacking a food:timeOfTheDay ; rdfs:label "snacking" . food:dinner a food:timeOfTheDay ; rdfs:label "dinner" . food:brand a owl:DatatypeProperty ; rdfs:label "Brand"@en; rdfs:comment "Food or beverage brand. The restaurants are not brand. When the 'brand' is not specified and, the food or beverage is very well-known (like 'Coca-Cola'), provide the brand name in 'brand', otherwise set 'brand' to ''."@en; rdfs:range xsd:string. food:company a owl:DatatypeProperty ; rdfs:label "Company"@en; rdfs:comment "Product company."@en; rdfs:range xsd:string. food:enumEvent a rdfs:Class . food:event a owl:DatatypeProperty ; rdfs:label "event"@en; rdfs:comment "Event of eating or drinking. Each must have an event"@en; rdfs:range food:enumEvent. food:intent a food:enumEvent ; rdfs:label "intent" . rdfs:comment "When the event should happen"@en. food:declaration a food:enumEvent ; rdfs:label "declaration" . rdfs:comment "When the event has already occured"@en. food:unknownEvent a food:enumEvent ; rdfs:label "unknown" ; rdfs:comment "When the event is unknown in the day"@en. """ ========================================================================================= ------------------------------ LLM Raw response ----------------------------- ```json [ { "name": "jambon", "quantity": "une tranche", "type": "food", "timeOfTheDay": "breakfast", "event": "declaration" }, { "name": "orange", "quantity": "une", "type": "food", "timeOfTheDay": "breakfast", "event": "declaration" } ] ``` ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ ```json [ { "name": "jambon", "quantity": "une tranche", "type": "food", "timeOfTheDay": "breakfast", "event": "declaration" }, { "name": "orange", "quantity": "une", "type": "food", "timeOfTheDay": "breakfast", "event": "declaration" } ] ``` ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "jambon", "quantity": "une tranche", "type": "food", "timeOfTheDay": "breakfast", "event": "declaration" }, { "name": "orange", "quantity": "une", "type": "food", "timeOfTheDay": "breakfast", "event": "declaration" }] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'jambon', 'quantity': 'une tranche', 'type': 'food', 'timeOfTheDay': 'breakfast', 'event': 'declaration'}, {'name': 'orange', 'quantity': 'une', 'type': 'food', 'timeOfTheDay': 'breakfast', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'jambon', 'quantity': 'une tranche', 'type': 'food', 'timeOfTheDay': 'breakfast', 'event': 'declaration'} First try: SELECT V_Name,V_Comment,V_NormName,V_NormComment,V_PackType,V_GTIN,V_GTINRef,V_ID,V_GlobalCount,V_NormTrademark,V_Trademark,V_NormAggr FROM KCALME_TABLE WHERE V_NormName LIKE '% jambon %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Jambon Cru - jambon cru - - - 9885 - - - CIQ#64b8482a5f9494f91650a6dfbb0cd41e Jambon Sec - jambon sec - - - 0 - - - CIQ#96c8fe38103fc721a15cfe55d6e25c6f Jambon Cru - jambon cru - fumé - - 268 - - - CIQ#5f3f73264b7c8e8500821bffaac09aee Jambon Sec - jambon sec - découenné, dégraissé - - 293 - - - CIQ#25959c69f01c1f2120ccc677017fa727 Jambon Cru - jambon cru - fumé, allégé en matière grasse - - 0 - - - CIQ#f647a53f900ffb0f8b6bcc1b9daac3fd Jambon Fumé - jambon fume - - - 1235 - - - KCA#b89a3b14af6277985c3d77e8a43fd3a7 Jambon Cuit - jambon cuit - fumé - - 130 - - - CIQ#17ca7e15b0319f1e287cbd0bcf02e149 Jambon Cuit - jambon cuit - choix - - 0 - - - CIQ#31a3ba17bd765304c35083900245a906 Jambon Cuit - jambon cuit - supérieur - - 879 - - - CIQ#62b09fb38df99e94d05d097272b0f943 Jambon Cuit - jambon cuit - choix, avec couenne - - 0 - - - CIQ#c197beb44fda0f03581cdd01ee751078 Jambon Cuit - jambon cuit - supérieur, découenné - - 0 - - - CIQ#a4feb0298e2ed9bf7086021f843d5542 Jambon Cuit - jambon cuit - supérieur, avec couenne - - 0 - - - CIQ#44f954aa2607fc98de99e42c7a2f34f0 Jambon Cuit - jambon cuit - choix, découenné dégraissé - - 0 - - - CIQ#1bdbfa77737e32f3afd8b85235c13da8 Jambon Cuit - jambon cuit - de Paris, découenné dégraissé - - 0 - - - CIQ#2204461860d60e77475581012d525590 Jambon Cuit - jambon cuit - supérieur, découenné dégraissé - - 0 - - - CIQ#7fe80de772280767444b552c0124ab0f Jambon Cuit - jambon cuit - supérieur, à teneur réduite en sel - - 0 - - - CIQ#f6e3b7457066170ebc96fe96171fba23 Jambon Blanc - jambon blanc - - - 41088 - - - KCA#a2c3580fad4917288fe40406fb88cadb Jambon Bayonne - jambon bayonne - - - 2108 - - - KCA#a7501ed926d61fc6282a9dc417593554 Jambon Persillé - jambon persille - - - 315 - - - KCA#a68e12a46f2795c6c267b411dd8111f4 Jambon de Poulet - jambon de poulet - - - 5421 - - - KCA#8a8c7fe60575ff37bd0a2f58c58a75a0 ---------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'orange', 'quantity': 'une', 'type': 'food', 'timeOfTheDay': 'breakfast', 'event': 'declaration'} First try: SELECT V_Name,V_Comment,V_NormName,V_NormComment,V_PackType,V_GTIN,V_GTINRef,V_ID,V_GlobalCount,V_NormTrademark,V_Trademark,V_NormAggr FROM KCALME_TABLE WHERE V_NormName LIKE '% orange %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Orange - orange - pulpe, crue - - 19789 - - - CIQ#a84ec3c1b9bc46c10b639fa15eeef5f4 Orange Givrée - orange givree - - - 31 - - - KCA#78bd77a68826904b6b891043ddcc9d5a Orange Pressée - orange pressee - - - 3137 - - - KCA#d951c9057cfe647b69b7f30181322ad1 Jus d'Orange - ju orange - - - 52983 - - - KCA#da7a1f81a8cd82dbbbbbedf56a167258 Jus d'Orange - ju orange - pur jus - - 0 - - - CIQ#a4328be11b7e0fb0c4474532724cf38f Jus d'Orange - ju orange - à base de concentré - - 0 - - - CIQ#72928c242781a6ee15266175037b3fb8 Jus d'Orange Pasteurisé - ju orange pasteurise - - - 44 - - - KCA#8dc9e7ac955777e77122f7bd97350613 Jus d'Orange et Gingembre - ju orange gingembre - - - 31 - - - KCA#ac517779183d5fdeff117cfe8eb4be98 Jus d'Orange, Mangue et Fraise - ju orange mangue fraise - - - 60 - - - KCA#12cc18043b0813e5110bb808101edc8e Jus Orange Pamplemousse Pressés - ju orange pamplemousse presse - - - 517 - - - KCA#e606e760b12355e0cc070fbf069b4261 Jus d'Orange, Carotte et Céleri - ju orange carotte celeri - - - 117 - - - KCA#ba4cb33c47a671db82eeaad9ddd5c63e Jus d'Orange, Gingembre et Ananas - ju orange gingembre anana - - - 6 - - - KCA#e2edd8bdeebd69177ece6caee7f071d8 Jus d'Orange, Carotte et Gingembre - ju orange carotte gingembre - - - 73 - - - KCA#0c209cbc5beac761ddcf7ea316e5b29e Jus d'Orange, Ananas et Glace au Melon - ju orange anana glace melon - - - 21 - - - KCA#3e4e71456576da23059304f3eba50c9c Gin Orange - gin orange - - - 11 - - - KCA#69422eafcd803a4841e22ba7a24dbeaf Vodka Orange - vodka orange - - - 303 - - - KCA#afee6734db3389d9a53ba62d8e345e8e Tarte à l'Orange - tarte orange - à l'orange - - 0 - - - KCA#8cf553da1e0c3135218833739419ea98 Salade d'Oranges - salade orange - - - 71 - - - KCA#a7fe61d6cb0d6c12eba4ca95e0f74781 Dorade à l'Orange - dorade orange - - - 76 - - - KCA#f37ceb94004879aa0221259fea9ea8bd Canard à l'Orange - canard orange - - - 33 - - - KCA#42651abfdc29355ec0cf7e410b802f1a ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': "Ce matin j'ai mangé une tranche de jambon et une orange", 'intents': ['Identify food consumption or declaration'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Jambon Cru', 'normName': ' jambon cru ', 'comment': '', 'normComment': '', 'rank': 9885, 'id': 'CIQ#64b8482a5f9494f91650a6dfbb0cd41e', 'quantity': 'une tranche', 'quantityLem': '1 tranche', 'pack': ['TR3.w25'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'breakfast', 'event': 'declaration', 'serving': 'TR3-100', 'posiNormName': 0}, {'name': 'Orange', 'normName': ' orange ', 'comment': 'pulpe, crue', 'normComment': ' pulpe crue ', 'rank': 19789, 'id': 'CIQ#a84ec3c1b9bc46c10b639fa15eeef5f4', 'quantity': 'une', 'quantityLem': '1', 'pack': ['ORA.w200'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'breakfast', 'event': 'declaration', 'serving': 'ORA-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.5871803760528564} ---------------------------------------------------------------------------------- LLM CPU Time: 2.5871803760528564