Triple

T3638063
Position Surface form Disambiguated ID Type / Status
Subject Tostitos E77118 entity
Predicate flavorVariety P41829 FINISHED
Object Cantina Thin & Crispy
Cantina Thin & Crispy is a Tostitos tortilla chip variety known for its light, restaurant-style texture ideal for dipping and snacking.
 E77118 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Cantina Thin & Crispy | Statement: [Tostitos, flavorVariety, Cantina Thin & Crispy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cantina Thin & Crispy
Context triple: [Tostitos, flavorVariety, Cantina Thin & Crispy]
  • A. Tostitos
    Tostitos is a popular American brand of tortilla chips and related snack foods produced by Frito-Lay.
  • B. Prego
    Prego is a popular American brand of pasta sauces known for its thick, tomato-based varieties and wide range of flavors.
  • C. In & Out
    "In & Out" is a 1997 American comedy film about a small-town teacher whose life is upended when a former student publicly questions his sexuality, featuring a supporting performance by Debbie Reynolds.
  • D. Spic-O-Rama
    Spic-O-Rama is a one-man stage show by John Leguizamo in which he portrays multiple Latino characters in a fast-paced, comedic exploration of family and cultural identity.
  • E. TACO
    TACO is a peer-reviewed scientific journal published by the ACM that focuses on research in computer architecture and code optimization.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Cantina Thin & Crispy
Triple: [Tostitos, flavorVariety, Cantina Thin & Crispy]
Generated description
Cantina Thin & Crispy is a Tostitos tortilla chip variety known for its light, restaurant-style texture ideal for dipping and snacking.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cantina Thin & Crispy
Target entity description: Cantina Thin & Crispy is a Tostitos tortilla chip variety known for its light, restaurant-style texture ideal for dipping and snacking.
  • A. Tostitos chosen
    Tostitos is a popular American brand of tortilla chips and related snack foods produced by Frito-Lay.
  • B. Prego
    Prego is a popular American brand of pasta sauces known for its thick, tomato-based varieties and wide range of flavors.
  • C. In & Out
    "In & Out" is a 1997 American comedy film about a small-town teacher whose life is upended when a former student publicly questions his sexuality, featuring a supporting performance by Debbie Reynolds.
  • D. Spic-O-Rama
    Spic-O-Rama is a one-man stage show by John Leguizamo in which he portrays multiple Latino characters in a fast-paced, comedic exploration of family and cultural identity.
  • E. TACO
    TACO is a peer-reviewed scientific journal published by the ACM that focuses on research in computer architecture and code optimization.
  • F. None of above.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ad85dd0be48190b738990cb20c4731 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc328e5e481909d26318c743bc84a completed March 8, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b44f23298481909d313d6b3f8013cd completed March 13, 2026, 5:53 p.m.
NEDg Description generation batch_69b450785378819090b4ed7536db7757 completed March 13, 2026, 5:59 p.m.
NED2 Entity disambiguation (via description) batch_69b45a0afef8819097c6e87127b4d1db completed March 13, 2026, 6:40 p.m.
Created at: March 8, 2026, 3:24 p.m.