Triple

T10390652
Position Surface form Disambiguated ID Type / Status
Subject Monsters vs. Aliens E244883 entity
Predicate writtenBy P806 FINISHED
Object Maya Forbes E488234 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: Maya Forbes | Statement: [Monsters vs. Aliens, writtenBy, Maya Forbes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maya Forbes
Context triple: [Monsters vs. Aliens, writtenBy, Maya Forbes]
  • A. Maya Forbes chosen
    Maya Forbes is an American screenwriter, director, and producer known for films such as "Infinitely Polar Bear" and for her work on television series like "The Larry Sanders Show."
  • B. Maya Bishop
    Maya Bishop is a driven and skilled firefighter and former Olympic athlete who serves as a central protagonist and eventual captain on the television drama "Station 19."
  • C. Maya Imhoof
    Maya Imhoof is a film producer best known for her work on the acclaimed Swiss drama "The Boat Is Full."
  • D. Maya Vidal
    Maya Vidal is the troubled teenage protagonist of Isabel Allende’s novel "Maya’s Notebook," whose coming-of-age journey unfolds through her candid, reflective diary entries.
  • E. Maia Wilson
    Maia Wilson is an American singer and actress best known for her work in musical theatre and as a voice performer in film and television.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9b4f7d08190bcb16d3b4c8f22ad completed April 7, 2026, 11:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69d87e7adc3881909731d5289f370b8b completed April 10, 2026, 4:37 a.m.
Created at: April 6, 2026, 12:06 p.m.