Triple

T2071781
Position Surface form Disambiguated ID Type / Status
Subject Luisa E44829 entity
Predicate hasDiminutive P456 FINISHED
Object Luisita
Luisita is a Spanish feminine given name, typically used as a diminutive or affectionate form of Luisa.
E231556 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: Luisita | Statement: [Luisa, hasDiminutive, Luisita]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luisita
Context triple: [Luisa, hasDiminutive, Luisita]
  • A. Peñaflor
    Peñaflor is a Chilean town and commune located in the outskirts of Santiago, known for its residential character and green areas.
  • B. Enma Castro
    Enma Castro is a member of the Castro family of Cuba, known primarily as a sister of revolutionary leaders Raúl and Fidel Castro.
  • C. Mariquita
    Mariquita is a historic town in central Colombia known as an early colonial settlement and former mining center.
  • D. Amada Cruz
    Amada Cruz is an American museum director and arts administrator known for leading major art institutions, including serving as director of the Seattle Art Museum.
  • E. Francisca
    Francisca is a feminine given name, used in various European and Latin American cultures, that is cognate with the English name Frances.
  • 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: Luisita
Triple: [Luisa, hasDiminutive, Luisita]
Generated description
Luisita is a Spanish feminine given name, typically used as a diminutive or affectionate form of Luisa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Luisita
Target entity description: Luisita is a Spanish feminine given name, typically used as a diminutive or affectionate form of Luisa.
  • A. Peñaflor
    Peñaflor is a Chilean town and commune located in the outskirts of Santiago, known for its residential character and green areas.
  • B. Enma Castro
    Enma Castro is a member of the Castro family of Cuba, known primarily as a sister of revolutionary leaders Raúl and Fidel Castro.
  • C. Mariquita
    Mariquita is a historic town in central Colombia known as an early colonial settlement and former mining center.
  • D. Amada Cruz
    Amada Cruz is an American museum director and arts administrator known for leading major art institutions, including serving as director of the Seattle Art Museum.
  • E. Francisca
    Francisca is a feminine given name, used in various European and Latin American cultures, that is cognate with the English name Frances.
  • 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_69a88916c2b48190a5ca2e9b12cad3ed completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abba0d20bc8190b19a32157f8b1607 completed March 7, 2026, 5:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae272bd51881909b7da12925195417 completed March 9, 2026, 1:49 a.m.
NEDg Description generation batch_69ae28e6d8fc8190b5c0215607214b41 completed March 9, 2026, 1:56 a.m.
NED2 Entity disambiguation (via description) batch_69ae29556978819082f771e0723c4f0b completed March 9, 2026, 1:58 a.m.
Created at: March 4, 2026, 7:41 p.m.