JackyChunKit/Qwen3_SFT_Post huggingface dataset:
Task: Query_Product_Rank

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Evaluate the relevance of each product title in the input to the given query, and then sort the products in descending order of relevance, placing the most relevant product at the top of the ranked list.

Input:
Query: husqvarna 455 rancher 20 inch bar
Product list:
A: Husqvarna OEM 585943280 / 20" Pixel Sprocket Nose Chainsaw Bar / Drive Links 80, Pitch .325", Gauge .050"
B: Husqvarna 100000107 Powerbox Chainsaw Carrying Case for 455 Rancher, 460, 372XP and 575XP


assistant
Answer: B,A
Task: Query_Product_Rank

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Evaluate the relevance of each product title in the input to the given query, and then sort the products in descending order of relevance, placing the most relevant product at the top of the ranked list.

Input:
Query: 1 3/4 inch tooled belt strap without belt buckle
Product list:
A: TB105 Western X-Laced Genuine Full Grain Leather Belt Strap with Snaps on 1-3/4"(45mm) Wide (BRN,44)
B: Belt for buckle Western full grain Leather Engraved Tooled Strap w/Snaps for Interchangeable Buckles, USA,2022-06, size 46


assistant
Answer: A,B
Task: Product_Relation_Prediction

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Given the title of two products, predict if the two products are similar, if the two products will be purchased or viewed together. Answer only from the options.

Input:
Product 1: Goose Tureen w/ Ladel
Product 2: Toulouse Collection, Tureen with Ladle

Options:
A: Users who buy product 1 may also buy product 2.
B: Users who view product 1 may also view product 2.
C: The product 1 is similar with the product 2.


assistant
Answer: B
Task: Query_Product_Rank

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Rank the products A, B, C, ... based on their relevance to the provided query, and produce a ranked list with the most relevant product positioned at the top of the list.

Input:
Query: the incredibles heroes
Product list:
A: A Soldier's Secret: The Incredible True Story of Sarah Edmonds, a Civil War Hero
B: AQTOPS Incredibles Costumes for Girls Halloween Super Hero Dress Sets
C: Disney Infinity: Marvel Super Heroes (2.0 Edition) MARVEL'S The Avengers Figure Pack - Not Machine Specific


assistant
Answer: B,C,A
Task: Query_Product_Rank

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Given a query and a list of products denoted as A, B, C, ... with their titles, rank the products according to their relevance to the query. Output only a ranked list in which the most relevant product is at the top of the list.

Input:
Query: crewneck sweatshirt
Product list:
A: Hanes Men's EcoSmart Sweatshirt, Light Steel, Medium
B: Hanes Men's Pullover EcoSmart Hooded Sweatshirt, Deep Royal, Small


assistant
Answer: A,B
Task: Sentiment_Analysis

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Given the user's review, identify the user's sentiment from the listed options. Answer using one of the options.

Input:
User Review: I love these shears which I actually use for trimming my plants and flowers - they are expensive but very good quality and should last for many years...

Options:
A: very positive
B: positive
C: neutral
D: negative
E: very negative


assistant
Answer: A: very positive
Task: Product_Substitute_Identification

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Check if a product can function as a substitute for a given query, even if it doesn't fully meet all requirements. Output yes if it can or no otherwise.

Input:
Query: refurbished ue megablast
Product: Ultimate Ears UE MEGABOOM Wireless Bluetooth Speaker Waterproof and Shockproof - Lava Red (Renewed)


assistant
Answer: no
Task: Product_Substitute_Identification

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Given a query and a product, identify if the product is somewhat relevant to the query. It fails to fulfill some aspects of the query but the product can be used as a functional substitute. Only output yes or no.

Input:
Query: small window curtains checkered
Product: VERTKREA Stripe Window Curtain Striped Room Window Treatment Grommet Curtains 52  63 Inches Stripes Drapes for Bedroom Living Room, Black, Set of 2 Panels


assistant
Answer: no
Task: Multiclass_Product_Classification

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Evaluate the relevance between the query and product title, and choose the most accurate option from the given options.

Input:
Query: childs fold out couch bed
Product: Jaxx Zipline Modular Kids Loveseat & Ottomans/Fold Out Lounger, Charcoal

Options:
A: The product is relevant to the query, and satisfies all the query specifications.
B: The product is somewhat relevant. It fails to fulfill some aspects of the query but the product can be used as a functional substitute.
C: The product does not fulfill the query, but could be used in combination with a product exactly matching the query.
D: The product is irrelevant to the query.


assistant
Answer: A: The product is relevant to the query, and satisfies all the query specifications.
Task: Query_Product_Rank

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Rank the products A, B, C, ... based on their relevance to the provided query, and produce a ranked list with the most relevant product positioned at the top of the list.

Input:
Query: nike shorts men with pockets
Product list:
A: Nike Men's Team Fly Dri-FIT Shorts (Royal/Matte Silver, X-Large)
B: Nike Dri-FIT Icon, Men's Basketball Shorts, Athletic Shorts with Side Pockets, Black/Black/White, XL


assistant
Answer: B,A
Task: Sentiment_Analysis

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Given the user's review, identify the user's sentiment from the listed options. Answer using one of the options.

Input:
User Review: Functional stove, made in China and it feels like it.  Cheap price, so that is what you get.

Options:
A: very positive
B: positive
C: neutral
D: negative
E: very negative


assistant
Answer: C: neutral
Task: Product_Relation_Prediction

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Predict whether two products are similar, whether two products are likely to be purchased or viewed together based on their titles. Choose your answer from the provided options.

Input:
Product 1: IndiaCraft 15th Century Hand-And-A-Half Full Tang Tempered Battle Ready Hand Forged Sharp Sword
Product 2: Sir William Wallace Sword Brass - Claymore Medieval Sword With Scabbard

Options:
A: Users who buy product 1 may also buy product 2.
B: Users who view product 1 may also view product 2.
C: The product 1 is similar with the product 2.


assistant
Answer: B
Task: Sentiment_Analysis

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Determine the sentiment expressed by the user in her review from the provided choices, and respond by selecting one of the available options.

Input:
User Review: Seemed to be good quality and do the job. I am not an expert, so I bought one in a mid price range and was pleased until my Sigma 18-250 mm lens died after only 15 months (so warranty gone) Lens never seemed "right" from the start but completely dying in 15 months is the pits. So I can recommend the filter but not the lens

Options:
A: very positive
B: positive
C: neutral
D: negative
E: very negative


assistant
Answer: B: positive
Task: Query_Product_Rank

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Given a query and a list of products denoted as A, B, C, ... with their titles, rank the products according to their relevance to the query. Output only a ranked list in which the most relevant product is at the top of the list.

Input:
Query: 06 titan trans oil cooler line not adapter
Product list:
A: Four Seasons 53015 Transmission Oil Cooler Hose, 54-Inch
B: Lisle 39660 1/2" x 3/8" Transmission Oil Cooler Line Scissor


assistant
Answer: A,B
Task: Sentiment_Analysis

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Assess the user's sentiment in the provided review and select the appropriate sentiment option from the list as the answer.

Input:
User Review: The Nikon Coolpix 800 sounded like a great buy in a full-featured digital camera. Unfortunately, when mine arrived at my doorstep, after unpacking it and following the quick-start instructions to the letter, I took one test  photo, and the camera began to buzz and an ominous statement "system  error" flashed on the LCD screen. The only way I could even shut off  the camera was to open the battery bay. The comprehensive manual on CD said  that if this message appeared and a restart didn't fix the problem (it  didn't), the only action was to phone Nikon. Since this was a new camera,  right out of the box, I didn't bother, but packed it back up and returned  it the following day.  There are many good things about the camera, but in  my short time with it, other than the obvious fatal flaw, I noticed that  the battery compartment cover and smartcard cover were both very flimsy  (noted in other reviews). I feel that both of these will get extensive use  during the life of the camera and are prone to failure. Perhaps the major  fault was a fluke, but I won't be replacing this with another coolpix, or  probably with another Nikon.

Options:
A: very positive
B: positive
C: neutral
D: negative
E: very negative


assistant
Answer: E: very negative
Task: Query_Product_Rank

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Evaluate the relevance of each product title in the input to the given query, and then sort the products in descending order of relevance, placing the most relevant product at the top of the ranked list.

Input:
Query: potting soil without fertilizer
Product list:
A: Noot Organic Indoor Plant Soilless Potting Mix Coconut Coir Perlite Pre-Hydrated Root Stimulant Mycorrhizae Fertilizer. Houseplant, Aroid, Succulent, Monstera, Orchid, Fiddle Leaf Fig, Cactus. 1 Gal.
B: Organic Potting Soil for Indoor/Outdoor Plants, Expands to Fit 3 Inch and 4 Inch Pots - 12 Pack


assistant
Answer: B,A
Task: Product_Substitute_Identification

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Check if a product can function as a substitute for a given query, even if it doesn't fully meet all requirements. Output yes if it can or no otherwise.

Input:
Query: baby dolls for 2 year old girls
Product: 11 inch Soft Body Doll in Gift Box - Award Winner & Toy 11" Baby Doll (Caucasian)


assistant
Answer: no
Task: Query_Product_Rank

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Analyze the query and each product title. Sort the products in descending order based on their relevance to the query. The most relevant product should be at the top of the list, and output the ranked list.

Input:
Query: scooter mitts
Product list:
A: Docooler Cycling Handlebar Mittens Neoprene Rainproof MTB Motor Bar End Mitts Gloves Mountain Bike Hands Covers
B: MOVTOTOP Knee Pads for Kids, Soft Kids Knee and Elbow Pads with Gloves Set-Reinforced Stitching Around, Toddler Sports Protective Gear with Mesh Bag for Kids Skateboard Rollerblading Bike Scoote


assistant
Answer: A,B
Task: Product_Relation_Prediction

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Evaluate the titles of Product 1 and Product 2, then choose the option that best describes the relation between the two products.

Input:
Product 1: Cable Matters Rackmount or Wallmount 48-Port Cat6 RJ45 Patch Panel
Product 2: Intellinet Cat6 RJ45 UTP Stranded Modular Plugs, 100 Pack (502344)

Options:
A: Users who buy product 1 may also buy product 2.
B: Users who view product 1 may also view product 2.
C: The product 1 is similar with the product 2.


assistant
Answer: A
Task: Query_Product_Rank

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Evaluate each product title in the given list, assess its relevance to the given query, and then arrange the products in descending order of relevance, with the most relevant product at the top of the ranked list.

Input:
Query: black chip paint
Product list:
A: FixAuto  Touch Up Paint Brushes Lint Free, Small Paint Brushes for Touch Ups, 100 pcs Disposable Fine Micro Applicator Automotive/ Appliance Car Paint Chip Repair Detailing Touchups
B: Car Paint Repair Pearl White for T-oyota R-AV4 Anti-rust Auto Paint Scratch Remover Pen Touchup Paint for Cars Automotive Scratch Remover and Paint Restorer Auto Touch-up Paint (White Pearl)


assistant
Answer: B,A
Task: Product_Substitute_Identification

system
You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively. 
Below is an instruction that describes a task. After thinking, when you finally reach a conclusion based on the customer's intention, desire and belief, clearly state the BDI thinking process within <think> </think> and then the answer within <answer> </answer> tags.


user 
Instruction: Answer yes if the product is a substitute for the query and no otherwise.

Input:
Query: runts candy
Product: Assorted Candy Party Mix, 5 LB - Bulk Candy - Fun Size Skittles, Top Box Pop Taffy Pops, Fun Dip, and Much More!


assistant
Answer: yes