Triple

T4891897
Position Surface form Disambiguated ID Type / Status
Subject Maria Paola E109582 entity
Predicate hasComponent P35 FINISHED
Object Maria unclear NED1 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: Maria | Statement: [Maria Paola, hasComponent, Maria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maria
Context triple: [Maria Paola, hasComponent, Maria]
  • A. Maria
    Maria is an alternate given name of Letizia Ramolino, the mother of Napoleon Bonaparte and a notable figure in Corsican and French history.
  • B. Maria
    Maria is a female given name of Latin origin meaning "beloved" or "wished-for child," widely used across many cultures and languages.
  • C. Maria
    Maria is the protagonist of Paulo Coelho's novel "Eleven Minutes," a young Brazilian woman whose journey explores themes of love, sexuality, and self-discovery.
  • D. Maria
    Maria is the young Puerto Rican woman at the heart of the musical "West Side Story," whose forbidden romance with Tony drives the story’s modern retelling of "Romeo and Juliet."
  • E. Maria
    Maria is the middle given name of Cesare Maria De Vecchi, an Italian Fascist politician and prominent figure in Mussolini’s regime.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69bd4410bbf88190aad50d2451c863d6 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6e2444dc819088d5562e90d16d9b completed March 20, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69be81b9ab4c81909173686a76d32a88 completed March 21, 2026, 11:32 a.m.
Created at: March 20, 2026, 1:28 p.m.