Triple

T2082669
Position Surface form Disambiguated ID Type / Status
Subject Remy’s Ratatouille Adventure E45277 entity
Predicate featuresCharacter P626 FINISHED
Object Linguini
Linguini is the clumsy yet kind-hearted young chef from Disney-Pixar’s Ratatouille who secretly teams up with the rat Remy to create extraordinary dishes.
 E232244 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: Linguini | Statement: [Remy’s Ratatouille Adventure, featuresCharacter, Linguini]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Linguini
Context triple: [Remy’s Ratatouille Adventure, featuresCharacter, Linguini]
  • A. Meatballs
    Meatballs is a 1979 comedy film that helped establish Bill Murray as a major comedic star through his role as an irreverent summer camp counselor.
  • B. Alvito
    Alvito is a small Portuguese municipality in the Alentejo region, known for its historic castle and traditional rural landscape.
  • C. Alfredo
    Alfredo is a masculine given name, commonly used in Italian, Spanish, and Portuguese-speaking countries, derived from the name Alfred.
  • D. Prego
    Prego is a popular American brand of pasta sauces known for its thick, tomato-based varieties and wide range of flavors.
  • E. Bruschi
    Bruschi is the surname of Tedy Bruschi, a former NFL linebacker best known for his career with the New England Patriots.
  • 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: Linguini
Triple: [Remy’s Ratatouille Adventure, featuresCharacter, Linguini]
Generated description
Linguini is the clumsy yet kind-hearted young chef from Disney-Pixar’s Ratatouille who secretly teams up with the rat Remy to create extraordinary dishes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Linguini
Target entity description: Linguini is the clumsy yet kind-hearted young chef from Disney-Pixar’s Ratatouille who secretly teams up with the rat Remy to create extraordinary dishes.
  • A. Meatballs
    Meatballs is a 1979 comedy film that helped establish Bill Murray as a major comedic star through his role as an irreverent summer camp counselor.
  • B. Alvito
    Alvito is a small Portuguese municipality in the Alentejo region, known for its historic castle and traditional rural landscape.
  • C. Alfredo
    Alfredo is a masculine given name, commonly used in Italian, Spanish, and Portuguese-speaking countries, derived from the name Alfred.
  • D. Prego
    Prego is a popular American brand of pasta sauces known for its thick, tomato-based varieties and wide range of flavors.
  • E. Bruschi
    Bruschi is the surname of Tedy Bruschi, a former NFL linebacker best known for his career with the New England Patriots.
  • F. None of above. chosen

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_69a8891869c88190a02643e3bb746f59 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abba5097ac8190a723a8af2982238c completed March 7, 2026, 5:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae273d3f5881909fa6d935fa85c225 completed March 9, 2026, 1:49 a.m.
NEDg Description generation batch_69ae2a5767388190b16c0d2ce3af647c completed March 9, 2026, 2:03 a.m.
NED2 Entity disambiguation (via description) batch_69ae2b5ff1b88190a9754f0e892b6607 completed March 9, 2026, 2:07 a.m.
Created at: March 4, 2026, 7:41 p.m.