Triple

T16063434
Position Surface form Disambiguated ID Type / Status
Subject Erich Hoeber E389670 entity
Predicate notableWork P4 FINISHED
Object Red
"Red" is a 2010 action-comedy film about retired black-ops agents forced back into the field, known for its ensemble cast and blend of humor and high-octane espionage.
E1016355 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: [Erich Hoeber, notableWork, Red]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Red
Context triple: [Erich Hoeber, notableWork, Red]
  • A. Red
    Red is the nickname of William L. "Red" Whittaker, a pioneering American roboticist known for his work in field robotics and autonomous vehicles.
  • B. Red
    Red is Taylor Swift’s critically acclaimed 2012 studio album that marked her transition from country to mainstream pop with emotionally charged, genre-blending songs.
  • C. Red
    Red is the tough, sharp-tongued Russian matriarch and prison cook from the television series "Orange Is the New Black."
  • D. Red
    Red is Virgin America’s signature in-flight entertainment system, offering passengers on-demand movies, TV, music, games, and other interactive services.
  • E. Red
    "Red" is a song featured on the album *Careful Confessions* by singer-songwriter Sara Bareilles.
  • 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: [Erich Hoeber, notableWork, Red]
Generated description
"Red" is a 2010 action-comedy film about retired black-ops agents forced back into the field, known for its ensemble cast and blend of humor and high-octane espionage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Red
Target entity description: "Red" is a 2010 action-comedy film about retired black-ops agents forced back into the field, known for its ensemble cast and blend of humor and high-octane espionage.
  • A. Red chosen
    "Red" is a 2010 action-comedy film about retired black-ops agents forced back into the field, known for its ensemble cast led by Bruce Willis, Helen Mirren, Morgan Freeman, and John Malkovich.
  • B. Red
    Red is a small, unicycle character from Pixar’s early animated short film "Red’s Dream."
  • C. 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.
  • D. Red
    Red is the short-tempered, red-feathered bird who serves as the central protagonist of the Angry Birds franchise and its film adaptations.
  • E. Red
    Red is the tough, sharp-tongued Russian matriarch and prison cook from the television series "Orange Is the New Black."
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1837b048881908326739bbede756f completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffe47ca9748190be24a490c3cf0e8c completed May 10, 2026, 1:50 a.m.
NEDg Description generation batch_69ffe50986b4819095bb9cd568fcf972 completed May 10, 2026, 1:53 a.m.
NED2 Entity disambiguation (via description) batch_69ffe56441b881909e3a97331e3821d2 completed May 10, 2026, 1:54 a.m.
Created at: April 10, 2026, 4:57 a.m.