Triple

T7076040
Position Surface form Disambiguated ID Type / Status
Subject Maria Dmitrievna Isaeva E164821 entity
Predicate givenName P17 FINISHED
Object Maria E103006 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 Dmitrievna Isaeva, givenName, Maria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maria
Context triple: [Maria Dmitrievna Isaeva, givenName, Maria]
  • A. Maria chosen
    Maria is a female given name of Latin origin meaning "beloved" or "wished-for child," widely used across many cultures and languages.
  • B. 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.
  • C. Maria
    Maria is a witty and sharp-tongued gentlewoman in Olivia’s household in Shakespeare’s comedy "Twelfth Night," known for her clever schemes and playful manipulation of other characters.
  • D. Maria
    Maria is a coastal municipality on Siquijor Island in the Philippines known for its rural communities and scenic seaside landscapes.
  • E. Maria
    Maria is a key character in the historical drama "Tulip Fever," serving as the young maid whose secret romance and pregnancy help drive the film’s central scheme and emotional stakes.
  • 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_69c6887cbc6c8190bdfac42d940f4d8a completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e4ebf4048190bf5d7156817f93a7 completed March 27, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c79468c7688190bf10433f05e77574 completed March 28, 2026, 8:42 a.m.
Created at: March 27, 2026, 2:40 p.m.