Triple

T15340632
Position Surface form Disambiguated ID Type / Status
Subject Matilde Calderón y González E366783 entity
Predicate givenName P17 FINISHED
Object Matilde E923787 NE FINISHED

How this triple was built (2 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: Matilde | Statement: [Matilde Calderón y González, givenName, Matilde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matilde
Context triple: [Matilde Calderón y González, givenName, Matilde]
  • A. Matilde chosen
    Matilde is a feminine given name of Spanish and Portuguese origin, related to the name Matilda and historically borne by various notable women.
  • B. Mathilda
    Mathilda is the young girl in the film "Léon: The Professional" who becomes the protégé of a solitary hitman after her family is murdered.
  • C. Mathilda
    Mathilda is the middle name of Elivera Mathilda Carlson Doud, the wife of former U.S. President Dwight D. Eisenhower.
  • D. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • E. Gisèle
    Gisèle is a feminine given name of French origin, commonly used in Francophone countries and beyond.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d85a1355608190a6673ddb67231d54 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e12eb7c8190944a260aa1aa9156 completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff0b41f130819082ea69ea535468ce completed May 9, 2026, 10:24 a.m.
Created at: April 10, 2026, 3:17 a.m.