Triple

T3407838
Position Surface form Disambiguated ID Type / Status
Subject Ivana Baquero E71817 entity
Predicate familyName P18 FINISHED
Object Baquero
Baquero is a Spanish surname most notably associated with actress Ivana Baquero, known for her role in the film "Pan's Labyrinth."
 E355298 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: Baquero | Statement: [Ivana Baquero, familyName, Baquero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Baquero
Context triple: [Ivana Baquero, familyName, Baquero]
  • A. Gamboa
    Gamboa is a small town in Panama best known for its location along the Panama Canal and its proximity to the surrounding rainforest and canal infrastructure.
  • B. Herrera
    Herrera is a common Spanish surname borne by numerous notable figures across sports, politics, arts, and other fields in the Spanish-speaking world.
  • C. Herrero
    Herrero is a Spanish occupational surname derived from the word for "blacksmith" or "smith."
  • D. Burque
    Burque is a colloquial nickname commonly used to refer to the city of Albuquerque, New Mexico.
  • E. Magaña
    Magaña is a Spanish-language surname of Hispanic origin borne by various notable individuals in Mexico and other Spanish-speaking countries.
  • 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: Baquero
Triple: [Ivana Baquero, familyName, Baquero]
Generated description
Baquero is a Spanish surname most notably associated with actress Ivana Baquero, known for her role in the film "Pan's Labyrinth."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Baquero
Target entity description: Baquero is a Spanish surname most notably associated with actress Ivana Baquero, known for her role in the film "Pan's Labyrinth."
  • A. Gamboa
    Gamboa is a small town in Panama best known for its location along the Panama Canal and its proximity to the surrounding rainforest and canal infrastructure.
  • B. Herrera
    Herrera is a common Spanish surname borne by numerous notable figures across sports, politics, arts, and other fields in the Spanish-speaking world.
  • C. Herrero
    Herrero is a Spanish occupational surname derived from the word for "blacksmith" or "smith."
  • D. Burque
    Burque is a colloquial nickname commonly used to refer to the city of Albuquerque, New Mexico.
  • E. Magaña
    Magaña is a Spanish-language surname of Hispanic origin borne by various notable individuals in Mexico and other Spanish-speaking countries.
  • 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_69ad85ac312481909e7027ced1456a9f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb8ede9c48190b13b0f5e7474e7fa completed March 8, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34bdaf06c8190a8102a4e3c728066 completed March 12, 2026, 11:27 p.m.
NEDg Description generation batch_69b34e486c3c81908e73c5b75baf119c completed March 12, 2026, 11:37 p.m.
NED2 Entity disambiguation (via description) batch_69b34fc420b08190baee678721b1b32c completed March 12, 2026, 11:44 p.m.
Created at: March 8, 2026, 3:15 p.m.