Triple

T17800422
Position Surface form Disambiguated ID Type / Status
Subject María del Carmen E444407 entity
Predicate shortForm P43 FINISHED
Object Maica
Maica is a feminine given name, commonly used as a diminutive or affectionate form of María del Carmen in Spanish-speaking cultures.
E1287723 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: Maica | Statement: [María del Carmen, shortForm, Maica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maica
Context triple: [María del Carmen, shortForm, Maica]
  • A. Ariela
    Ariela is a feminine given name, often considered a variant of Ariel, used in various cultures and languages.
  • B. Mia Ausa
    Mia Ausa is a young, kind-hearted magician and the daughter of the Magic Guild's leader in the role-playing game Lunar: The Silver Star.
  • C. Mikaela
    Mikaela is a feminine given name most prominently associated with American alpine ski champion Mikaela Shiffrin.
  • D. Mira Calix
    Mira Calix was an innovative South African-born, UK-based electronic composer and sound artist known for blending experimental electronics with classical instrumentation and multimedia installations.
  • E. Romina
    Romina is an Italian-American actress and singer best known as half of the pop duo Al Bano & Romina Power.
  • 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: Maica
Triple: [María del Carmen, shortForm, Maica]
Generated description
Maica is a feminine given name, commonly used as a diminutive or affectionate form of María del Carmen in Spanish-speaking cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Maica
Target entity description: Maica is a feminine given name, commonly used as a diminutive or affectionate form of María del Carmen in Spanish-speaking cultures.
  • A. Ariela
    Ariela is a feminine given name, often considered a variant of Ariel, used in various cultures and languages.
  • B. Mia Ausa
    Mia Ausa is a young, kind-hearted magician and the daughter of the Magic Guild's leader in the role-playing game Lunar: The Silver Star.
  • C. Mikaela
    Mikaela is a feminine given name most prominently associated with American alpine ski champion Mikaela Shiffrin.
  • D. Mira Calix
    Mira Calix was an innovative South African-born, UK-based electronic composer and sound artist known for blending experimental electronics with classical instrumentation and multimedia installations.
  • E. Romina
    Romina is an Italian-American actress and singer best known as half of the pop duo Al Bano & Romina Power.
  • 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_69d8b9efe370819095cd219b143ae727 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e487ff42108190b82ceb4466aa2dff completed April 19, 2026, 7:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a02f84095f48190985b20bc8f049e5b completed May 12, 2026, 9:52 a.m.
NEDg Description generation batch_6a02f9078e088190b2e84f219f7457ed completed May 12, 2026, 9:55 a.m.
NED2 Entity disambiguation (via description) batch_6a02f98c91a481909739f2a8a681286d completed May 12, 2026, 9:57 a.m.
Created at: April 10, 2026, 10:13 a.m.