Input path: /home/debian/html/nutritwin/output_llm/6728f6d2119c7/input.json Output path: /home/debian/html/nutritwin/output_llm/6728f6d2119c7/output.json Input text: Ce matin j'ai mangé deux tranches de pain viking avec du Fleury allégé et deux tranches de jambon. 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 deux tranches de pain viking avec du Fleury allégé et deux tranches de jambon. ================================================================================================================================== ==================================== 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 deux tranches de pain viking avec du Fleury allégé et deux tranches de jambon.###. 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 deux tranches de pain viking avec du Fleury allégé et deux tranches de jambon.""" 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 beverage identifier, the name should not contain information related to quantity or container (like glass...)."@en; rdfs:comment "Ignore food or beverage when it is not consumed in the past, now or in the future."@en; rdfs:comment "The cooking mode is not in the name. 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."@en; rdfs:comment "When the name is very known (ex: Activia, Coca) and the brand is not mentioned, guess the brand."@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": "pain viking", "quantity": "deux tranches", "type": "food", "time of the day": "breakfast", "event": "declaration" }, { "name": "Fleury allégé", "quantity": "", "type": "food", "time of the day": "breakfast", "event": "declaration" }, { "name": "jambon", "quantity": "deux tranches", "type": "food", "time of the day": "breakfast", "event": "declaration" } ] ``` ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ ```json [ { "name": "pain viking", "quantity": "deux tranches", "type": "food", "time of the day": "breakfast", "event": "declaration" }, { "name": "Fleury allégé", "quantity": "", "type": "food", "time of the day": "breakfast", "event": "declaration" }, { "name": "jambon", "quantity": "deux tranches", "type": "food", "time of the day": "breakfast", "event": "declaration" } ] ``` ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "pain viking", "quantity": "deux tranches", "type": "food", "time of the day": "breakfast", "event": "declaration" }, { "name": "Fleury allégé", "quantity": "", "type": "food", "time of the day": "breakfast", "event": "declaration" }, { "name": "jambon", "quantity": "deux tranches", "type": "food", "time of the day": "breakfast", "event": "declaration" }] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'pain viking', 'quantity': 'deux tranches', 'type': 'food', 'time of the day': 'breakfast', 'event': 'declaration'}, {'name': 'Fleury allégé', 'quantity': '', 'type': 'food', 'time of the day': 'breakfast', 'event': 'declaration'}, {'name': 'jambon', 'quantity': 'deux tranches', 'type': 'food', 'time of the day': 'breakfast', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'pain viking', 'quantity': 'deux tranches', 'type': 'food', 'time of the day': '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 '% pain viking %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) Second 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_NormAggr LIKE '% pain viking %' AND V_NormTrademark LIKE '%%' ------------------------------------------- ------ERROR-------------------------------- No solution for query: 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_NormAggr LIKE '% pain viking %' AND V_NormTrademark LIKE '%%' ------------------------------------------- ------------------------------------------- ----------- result to be analyzed ----------- {'name': 'Fleury allégé', 'quantity': '', 'type': 'food', 'time of the day': '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 '% fleury allege %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) Second 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_NormAggr LIKE '% fleury allege %' AND V_NormTrademark LIKE '%%' ------------------------------------------- ------ERROR-------------------------------- No solution for query: 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_NormAggr LIKE '% fleury allege %' AND V_NormTrademark LIKE '%%' ------------------------------------------- ------------------------------------------- ----------- result to be analyzed ----------- {'name': 'jambon', 'quantity': 'deux tranches', 'type': 'food', 'time of the day': '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 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': "Ce matin j'ai mangé deux tranches de pain viking avec du Fleury allégé et deux tranches de jambon.", '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': 'deux tranches', 'quantityLem': '2 tranche', 'pack': ['TR3.w25'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': 'TR3-200', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.7181577682495117} ---------------------------------------------------------------------------------- LLM CPU Time: 2.7181577682495117