Triple

T9967321
Position Surface form Disambiguated ID Type / Status
Subject Marisa E195715 entity
Predicate hasDiminutiveFormOf P456 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: [Marisa, hasDiminutiveFormOf, Maria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maria
Context triple: [Marisa, hasDiminutiveFormOf, 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_69ca82ebd1288190912f9e4482d1fa35 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb71f9d7c8190ac02c53052c1c6ad completed April 2, 2026, 12:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d257c002cc8190becc9730b2c01782 completed April 5, 2026, 12:38 p.m.
Created at: March 30, 2026, 8:47 p.m.