Triple

T6239455
Position Surface form Disambiguated ID Type / Status
Subject Kristin (TV series) E139561 entity
Predicate character P662 FINISHED
Object Mona E323562 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: Mona | Statement: [Kristin (TV series), character, Mona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mona
Context triple: [Kristin (TV series), character, Mona]
  • A. Mona chosen
    Mona is a feminine given name used in various cultures, often as a standalone name or a diminutive of names like Ramona or Simona.
  • B. Mona
    Mona is a residential and academic community in the Parish of St. Andrew, Jamaica, best known as the main campus location of the University of the West Indies.
  • C. MONA
    MONA is a renowned private art museum in Hobart, Tasmania, known for its provocative contemporary and ancient art collections and unconventional, immersive visitor experience.
  • D. Pauletta
    Pauletta is a feminine given name, typically considered a diminutive or variant of Paula or Pauline.
  • E. Mella
    Mella is a Spanish-language surname most notably associated with Cuban revolutionary leader Julio Antonio Mella.
  • 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_69c008b0e7ac8190808a59573ee646f3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063048df081909a13d16b6f6bf65d completed March 22, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20e01845081909c54fe938600be3e completed March 24, 2026, 4:07 a.m.
Created at: March 22, 2026, 4:23 p.m.