Triple

T4058867
Position Surface form Disambiguated ID Type / Status
Subject Josefa Ortiz de Domínguez E84759 entity
Predicate givenName P17 FINISHED
Object María
María is the given first name of Josefa Ortiz de Domínguez, a prominent figure in Mexico’s War of Independence.
 E411909 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: María | Statement: [Josefa Ortiz de Domínguez, givenName, María]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: María
Context triple: [Josefa Ortiz de Domínguez, givenName, María]
  • A. María
    "María" is a film featuring actress Taryn Power in a significant role.
  • B. María
    María is a key character in Ernest Hemingway's novel "For Whom the Bell Tolls," known as a young Spanish woman and love interest of the protagonist amid the Spanish Civil War.
  • C. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • D. Francisca
    Francisca is a feminine given name, used in various European and Latin American cultures, that is cognate with the English name Frances.
  • E. Manuela
    Manuela is the given name of Maria Manuela, a 16th-century Portuguese princess who became Queen of Castile through marriage to King Philip II of Spain.
  • 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: María
Triple: [Josefa Ortiz de Domínguez, givenName, María]
Generated description
María is the given first name of Josefa Ortiz de Domínguez, a prominent figure in Mexico’s War of Independence.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: María
Target entity description: María is the given first name of Josefa Ortiz de Domínguez, a prominent figure in Mexico’s War of Independence.
  • A. María
    María is a key character in Ernest Hemingway's novel "For Whom the Bell Tolls," known as a young Spanish woman and love interest of the protagonist amid the Spanish Civil War.
  • B. María
    "María" is a film featuring actress Taryn Power in a significant role.
  • C. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • D. Francisca
    Francisca is a feminine given name, used in various European and Latin American cultures, that is cognate with the English name Frances.
  • E. Manuela
    Manuela is the given name of Maria Manuela, a 16th-century Portuguese princess who became Queen of Castile through marriage to King Philip II of Spain.
  • 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_69aed933bec881909edfa28ebb69c634 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefbd13b4481908f9c09cc4f4a9724 completed March 9, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b562a6250081908f289f43b066b04d completed March 14, 2026, 1:29 p.m.
NEDg Description generation batch_69b563b3db0481909f3dd2a9e6a88e6e completed March 14, 2026, 1:33 p.m.
NED2 Entity disambiguation (via description) batch_69b567e223cc8190aa1d7e827e6c70fd completed March 14, 2026, 1:51 p.m.
Created at: March 9, 2026, 3:38 p.m.