Triple

T550605
Position Surface form Disambiguated ID Type / Status
Subject Pan’s Labyrinth E11830 entity
Predicate leadActor P1507 FINISHED
Object Maribel Verdú
Maribel Verdú is a Spanish actress acclaimed for her work in films such as "Pan’s Labyrinth" and "Y Tu Mamá También."
 E72383 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: Maribel Verdú | Statement: [Pan’s Labyrinth, leadActor, Maribel Verdú]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Maribel Verdú
Context triple: [Pan’s Labyrinth, leadActor, Maribel Verdú]
  • A. Isabelle Ferrer
    Isabelle Ferrer is a French woman best known for being the former wife of legendary footballer and actor Eric Cantona.
  • B. Claudia Castello
    Claudia Castello is a Brazilian film editor best known for her work on major feature films including the boxing drama "Creed."
  • C. Montserrat Caballé
    Montserrat Caballé was a renowned Spanish operatic soprano celebrated for her powerful yet delicate voice and exceptional bel canto technique.
  • D. Lupe Vélez
    Lupe Vélez was a Mexican-born Hollywood actress and comedian of the 1920s and 1930s, known for her vibrant screen presence and roles in both silent films and early talkies.
  • E. Margarita Isabel
    Margarita Isabel was a Mexican actress known for her work in film, television, and theater.
  • 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: Maribel Verdú
Triple: [Pan’s Labyrinth, leadActor, Maribel Verdú]
Generated description
Maribel Verdú is a Spanish actress acclaimed for her work in films such as "Pan’s Labyrinth" and "Y Tu Mamá También."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Maribel Verdú
Target entity description: Maribel Verdú is a Spanish actress acclaimed for her work in films such as "Pan’s Labyrinth" and "Y Tu Mamá También."
  • A. Isabelle Ferrer
    Isabelle Ferrer is a French woman best known for being the former wife of legendary footballer and actor Eric Cantona.
  • B. Claudia Castello
    Claudia Castello is a Brazilian film editor best known for her work on major feature films including the boxing drama "Creed."
  • C. Montserrat Caballé
    Montserrat Caballé was a renowned Spanish operatic soprano celebrated for her powerful yet delicate voice and exceptional bel canto technique.
  • D. Lupe Vélez
    Lupe Vélez was a Mexican-born Hollywood actress and comedian of the 1920s and 1930s, known for her vibrant screen presence and roles in both silent films and early talkies.
  • E. Margarita Isabel
    Margarita Isabel was a Mexican actress known for her work in film, television, and theater.
  • 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_69a4932941d08190815efd422f0b4ca7 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a499030cf4819089b9163102255e49 completed March 1, 2026, 7:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69a501bb88f88190b1de92ca77606d2f completed March 2, 2026, 3:19 a.m.
NEDg Description generation batch_69a503b501388190baed19e781c24b4d completed March 2, 2026, 3:27 a.m.
NED2 Entity disambiguation (via description) batch_69a5077cf14081909478ea1e0fd3eff5 completed March 2, 2026, 3:43 a.m.
Created at: March 1, 2026, 7:32 p.m.