Input path: /home/debian/html/nutritwin/output_llm/671a32745a613/input.json Output path: /home/debian/html/nutritwin/output_llm/671a32745a613/output.json Input text: Carottes cuites. 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: Carottes cuites. ================================================================================================================================== ==================================== 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: ###Carottes cuites.###. 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 : """Carottes cuites.""" 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": "Carottes", "cooking method": "cuites", "type of food": "food", "event": "declaration" } ] ``` ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ ```json [ { "name": "Carottes", "cooking method": "cuites", "type of food": "food", "event": "declaration" } ] ``` ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "Carottes", "cooking method": "cuites", "type of food": "food", "event": "declaration" }] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'Carottes', 'cooking method': 'cuites', 'type of food': 'food', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'Carottes', 'cooking method': 'cuites', 'type of food': 'food', '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 '% carotte %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Carotte - carotte - - - 0 - - - CIQ#c25a5ac9d76a886e8d048234775511cc Carotte - carotte - crue - - 1 - - - CIQ#a7874f4f33fb2dbc15824a2e825563a1 Carotte - carotte - purée - - 0 - - - CIQ#9c5ebd1506b8bd79c185157a907e5bdb Carotte - carotte - surgelée - - 45 - - - CIQ#e3009eb73fdd922e2253b10af6bfa6d9 Carotte - carotte - égouttée - - 0 - - - CIQ#949bbc6db954a7c778a54ae6468f63c7 Carotte - carotte - à la vapeur - - 0 - - - CIQ#1de710714c0199745f6629010e1f4b1b Carotte - carotte - purée cuisinée à la crème - - 0 - - - CIQ#32559c9674d3bad3a4340c9eae6501ad Carotte - carotte - bouillie/cuite à l'eau, fondante - - 0 - - - CIQ#82c4ed5b7b54f49bfca9f849a0c03b48 Carotte - carotte - bouillie/cuite à l'eau, croquante - - 0 - - - CIQ#5cd51d236a0a8e7c95564dd5f01f45d9 Carotte (jus) - carotte - - - 12544 - - - KCA#c25a5ac9d76a886e8d048234775511cc Carottes Vichy - carotte vichy - - - 2919 - - - KCA#c3d70e0599b5f9ed8f8c5855114d2920 Carottes Rapées - carotte rapee - - - 11844 - - - KCA#5bab4982631307ce183c664c08e55546 Carottes Rapées - carotte rapee - à l'Orange - - 32 - - - KCA#73ce70cd5efc3dc60888616fadfd35af Carottes Surgelées - carotte surgelee - - - 0 - - - KCA#13cc5a1b7bf3fb616eae70ea61518915 Carottes à l'Étuvée - carotte etuvee - - - 1807 - - - KCA#49cbbe74a431d4e41b8704d1fe93ec8e Carottes Râpées Nature - carotte rapee nature - - - 1074 - - - KCA#08362e84e9b96863e50aef4a65b95bf4 Carottes à la Fermière - carotte fermiere - - - 180 - - - KCA#84ed7da5773a27fe3972f5bfb0dbc423 Carotte Râpée à la Vinaigrette - carotte rapee vinaigrette - - - 1371 - - - KCA#550aab930f59f61f6d4b015c1f19f2a7 Soupe à la Carotte - soupe carotte - - - 4 - - - CIQ#caea7c027f921522fe3dfa8ae19f528d Flan aux Carottes - flan au carotte - - - 195 - - - KCA#aa67df5d93c0fe5f69f4a1cbc7b479be ---------------------------------------------------- ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution --------------------------------- final result ----------------------------------- {'prompt': 'Carottes cuites.', 'intents': ['Identify food consumption or declaration'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Carotte', 'normName': ' carotte ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'CIQ#c25a5ac9d76a886e8d048234775511cc', 'quantity': '', 'quantityLem': '', 'pack': ['CAR.w125'], 'type': '', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 1.3126373291015625} ---------------------------------------------------------------------------------- LLM CPU Time: 1.3126373291015625