Triple

T20493204
Position Surface form Disambiguated ID Type / Status
Subject Mi corazón es tuyo E502799 entity
Predicate castMember P1668 FINISHED
Object Rafael Inclán
Rafael Inclán is a veteran Mexican actor and comedian known for his extensive work in film and telenovelas.
E1546795 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: Rafael Inclán | Statement: [Mi corazón es tuyo, castMember, Rafael Inclán]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rafael Inclán
Context triple: [Mi corazón es tuyo, castMember, Rafael Inclán]
  • A. Miguel Inclán
    Miguel Inclán was a prominent Mexican character actor known for his memorable supporting roles in classic Mexican cinema of the 1940s and 1950s.
  • B. Guillermo Haro
    Guillermo Haro was a Mexican astronomer renowned for his pioneering work on star-forming regions and the co-discovery of Herbig–Haro objects.
  • C. Rafael Cerero
    Rafael Cerero was a Spanish representative involved in the negotiations that concluded the Spanish–American War with the 1898 Treaty of Paris.
  • D. Enrique Ávila
    Enrique Ávila is a Cuban artist best known for creating iconic large-scale facade artworks on prominent buildings in Havana.
  • E. Fernando Chacón
    Fernando Chacón was a Spanish naval officer best known for his role as a commander in early 18th-century Mediterranean maritime conflicts.
  • 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: Rafael Inclán
Triple: [Mi corazón es tuyo, castMember, Rafael Inclán]
Generated description
Rafael Inclán is a veteran Mexican actor and comedian known for his extensive work in film and telenovelas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rafael Inclán
Target entity description: Rafael Inclán is a veteran Mexican actor and comedian known for his extensive work in film and telenovelas.
  • A. Miguel Inclán
    Miguel Inclán was a prominent Mexican character actor known for his memorable supporting roles in classic Mexican cinema of the 1940s and 1950s.
  • B. Guillermo Haro
    Guillermo Haro was a Mexican astronomer renowned for his pioneering work on star-forming regions and the co-discovery of Herbig–Haro objects.
  • C. Rafael Cerero
    Rafael Cerero was a Spanish representative involved in the negotiations that concluded the Spanish–American War with the 1898 Treaty of Paris.
  • D. Enrique Ávila
    Enrique Ávila is a Cuban artist best known for creating iconic large-scale facade artworks on prominent buildings in Havana.
  • E. Fernando Chacón
    Fernando Chacón was a Spanish naval officer best known for his role as a commander in early 18th-century Mediterranean maritime conflicts.
  • 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_69e0b4b0373881909dd3e9387f82eab4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69cbb3bd081909351525208b41bba completed April 20, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0b5844337081908aef20e35afd6233 completed May 18, 2026, 6:19 p.m.
NEDg Description generation batch_6a0b6f5b85548190bd54f5a13dd27c5d completed May 18, 2026, 7:58 p.m.
NED2 Entity disambiguation (via description) batch_6a0b7072e43c8190ad8f8d09f61d3f7b completed May 18, 2026, 8:02 p.m.
Created at: April 16, 2026, 11:35 a.m.