Triple

T2200433
Position Surface form Disambiguated ID Type / Status
Subject Monster E50475 entity
Predicate editedBy P1954 FINISHED
Object J. M. R. Luna
J. M. R. Luna is an editor known for working on the publication titled "Monster."
E241136 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: J. M. R. Luna | Statement: [Monster, editedBy, J. M. R. Luna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: J. M. R. Luna
Context triple: [Monster, editedBy, J. M. R. Luna]
  • A. José Ybarra-Jaegar
    José Ybarra-Jaegar is a minor character in Truman Capote’s novella "Breakfast at Tiffany’s," appearing within Holly Golightly’s New York social circle.
  • B. William Miranda Torres
    William Miranda Torres is a Puerto Rican politician who serves as the mayor of the city of Caguas.
  • C. Joaquín Goyache
    Joaquín Goyache is a Spanish veterinarian and academic who serves as rector of the Complutense University of Madrid.
  • D. Guillermo Jullian de la Fuente
    Guillermo Jullian de la Fuente was a Chilean architect best known as a close collaborator of Le Corbusier and a key contributor to several of his late projects.
  • E. X. Atencio
    X. Atencio was a Disney animator and Imagineer best known for writing the iconic scripts and song lyrics for classic Disneyland attractions such as Pirates of the Caribbean and the Haunted Mansion.
  • 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: J. M. R. Luna
Triple: [Monster, editedBy, J. M. R. Luna]
Generated description
J. M. R. Luna is an editor known for working on the publication titled "Monster."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: J. M. R. Luna
Target entity description: J. M. R. Luna is an editor known for working on the publication titled "Monster."
  • A. José Ybarra-Jaegar
    José Ybarra-Jaegar is a minor character in Truman Capote’s novella "Breakfast at Tiffany’s," appearing within Holly Golightly’s New York social circle.
  • B. William Miranda Torres
    William Miranda Torres is a Puerto Rican politician who serves as the mayor of the city of Caguas.
  • C. Joaquín Goyache
    Joaquín Goyache is a Spanish veterinarian and academic who serves as rector of the Complutense University of Madrid.
  • D. Guillermo Jullian de la Fuente
    Guillermo Jullian de la Fuente was a Chilean architect best known as a close collaborator of Le Corbusier and a key contributor to several of his late projects.
  • E. X. Atencio
    X. Atencio was a Disney animator and Imagineer best known for writing the iconic scripts and song lyrics for classic Disneyland attractions such as Pirates of the Caribbean and the Haunted Mansion.
  • 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_69a88b044ab48190add007487680f009 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abbfa06bb4819092d7021358846e5f completed March 7, 2026, 6:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5dbb6e8481908610337cfd2a4bd1 completed March 9, 2026, 5:42 a.m.
NEDg Description generation batch_69ae5e4a45a08190bd96af6cda06ab35 completed March 9, 2026, 5:44 a.m.
NED2 Entity disambiguation (via description) batch_69ae5ec5a5b88190b80fc3607d2c789c completed March 9, 2026, 5:46 a.m.
Created at: March 4, 2026, 7:46 p.m.