Triple

T9740331
Position Surface form Disambiguated ID Type / Status
Subject Red's Dream E236169 entity
Predicate mainCharacter P1183 FINISHED
Object Red
Red is a small, unicycle character from Pixar’s early animated short film "Red’s Dream."
E818761 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: Red | Statement: [Red's Dream, mainCharacter, Red]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Red
Context triple: [Red's Dream, mainCharacter, Red]
  • A. Red
    Red is Virgin America’s signature in-flight entertainment system, offering passengers on-demand movies, TV, music, games, and other interactive services.
  • B. Red
    Red is the famous nickname of Arnold "Red" Auerbach, the legendary Boston Celtics coach and executive known for his pivotal role in building an NBA dynasty.
  • C. Red
    Red is one of the main playable heroes in the run-and-gun video game Gunstar Heroes, known for fast-paced combat and cooperative action.
  • D. Red
    Red is the nickname of Red Rolfe, an American Major League Baseball third baseman best known for his years with the New York Yankees in the 1930s and 1940s.
  • E. Red
    "Red" is a stage play by John Logan that dramatizes the life and work of abstract expressionist painter Mark Rothko, particularly his creation of the Seagram Murals.
  • 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: Red
Triple: [Red's Dream, mainCharacter, Red]
Generated description
Red is a small, unicycle character from Pixar’s early animated short film "Red’s Dream."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Red
Target entity description: Red is a small, unicycle character from Pixar’s early animated short film "Red’s Dream."
  • A. Red
    Red is a major character from the Pokémon franchise, known as the silent, highly skilled Pokémon Trainer who serves as the protagonist of the original games and a legendary opponent in later titles.
  • B. Red
    Red is a central character in Stephen King's novella "Rita Hayworth and Shawshank Redemption" and its film adaptation, known as the wise, long-term inmate who befriends Andy Dufresne.
  • C. Red
    Red is one of the main playable heroes in the run-and-gun video game Gunstar Heroes, known for fast-paced combat and cooperative action.
  • D. Red
    Red is the tough, sharp-tongued Russian matriarch and prison cook from the television series "Orange Is the New Black."
  • E. Red
    Red is the nickname of William L. "Red" Whittaker, a pioneering American roboticist known for his work in field robotics and autonomous vehicles.
  • 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_69ca84d313e88190983ee6ffd0ef60d2 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9f29a5bc8190b2b391017405c71e completed April 1, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1afe974608190874e2aba2189de80 completed April 5, 2026, 12:42 a.m.
NEDg Description generation batch_69d1b08ba1f48190830852f9d60e3368 completed April 5, 2026, 12:44 a.m.
NED2 Entity disambiguation (via description) batch_69d1b124659481909e7a2ecaf01d8a50 completed April 5, 2026, 12:47 a.m.
Created at: March 30, 2026, 8:22 p.m.