Triple

T13004281
Position Surface form Disambiguated ID Type / Status
Subject Raul Julia E322245 entity
Predicate notableWork P4 FINISHED
Object Romero
"Romero" is a 1989 biographical drama film starring Raúl Juliá as Salvadoran Archbishop Óscar Romero, depicting his transformation into a vocal human rights advocate during El Salvador's civil conflict.
 E915592 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: Romero | Statement: [Raul Julia, notableWork, Romero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Romero
Context triple: [Raul Julia, notableWork, Romero]
  • A. Romero
    Romero is a character from the family-oriented action-adventure film "Spy Kids 3-D: Game Over," part of the popular Spy Kids movie franchise.
  • B. Romero
    Romero is a common Spanish-origin surname borne by numerous notable individuals across fields such as sports, arts, and entertainment.
  • C. Raymundo
    Raymundo is a masculine given name, commonly used in Spanish- and Portuguese-speaking cultures, that is related to the name Ramón.
  • D. Gómez
    Gómez is a common Spanish surname widely found in Spain and Latin American countries.
  • E. Guzman
    Guzman is a Spanish surname of likely toponymic origin that has been borne by numerous notable figures across history and the Spanish-speaking world.
  • 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: Romero
Triple: [Raul Julia, notableWork, Romero]
Generated description
"Romero" is a 1989 biographical drama film starring Raúl Juliá as Salvadoran Archbishop Óscar Romero, depicting his transformation into a vocal human rights advocate during El Salvador's civil conflict.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Romero
Target entity description: "Romero" is a 1989 biographical drama film starring Raúl Juliá as Salvadoran Archbishop Óscar Romero, depicting his transformation into a vocal human rights advocate during El Salvador's civil conflict.
  • A. Romero
    Romero is a character from the family-oriented action-adventure film "Spy Kids 3-D: Game Over," part of the popular Spy Kids movie franchise.
  • B. Romero chosen
    Romero is a common Spanish-origin surname borne by numerous notable individuals across fields such as sports, arts, and entertainment.
  • C. Raymundo
    Raymundo is a masculine given name, commonly used in Spanish- and Portuguese-speaking cultures, that is related to the name Ramón.
  • D. Gómez
    Gómez is a common Spanish surname widely found in Spain and Latin American countries.
  • E. Guzman
    Guzman is a Spanish surname of likely toponymic origin that has been borne by numerous notable figures across history and the Spanish-speaking world.
  • 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_69d807657e8c8190bd9435ee2f823845 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e9a2a448190968833354280e474 completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c107f990819093042560b1bc4473 completed May 3, 2026, 3:29 a.m.
NEDg Description generation batch_69f6c43bc75c8190887b8135fbc8bbb5 completed May 3, 2026, 3:42 a.m.
NED2 Entity disambiguation (via description) batch_69f6c50cf3c08190b1ef6379f1f96201 completed May 3, 2026, 3:46 a.m.
Created at: April 9, 2026, 8:47 p.m.