Triple

T20498385
Position Surface form Disambiguated ID Type / Status
Subject Lux Lisbon E503232 entity
Predicate hasParent P120 FINISHED
Object Mrs. Lisbon NE NERFINISHED

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: Mrs. Lisbon | Statement: [Lux Lisbon, hasParent, Mrs. Lisbon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mrs. Lisbon
Context triple: [Lux Lisbon, hasParent, Mrs. Lisbon]
  • A. Therese Lisbon
    Therese Lisbon is one of the five Lisbon sisters at the center of Jeffrey Eugenides’ novel and Sofia Coppola’s film "The Virgin Suicides," whose cloistered suburban life and tragic fate are observed and mythologized by neighborhood boys.
  • B. Teresa Lisbon
    Teresa Lisbon is a tough, principled law enforcement agent who leads a California Bureau of Investigation team and serves as Patrick Jane’s grounded partner in the TV series "The Mentalist."
  • C. Mr. Lisbon chosen
    Mr. Lisbon is the strict, emotionally distant father of the Lisbon sisters in Jeffrey Eugenides’ novel "The Virgin Suicides."
  • D. Bonnie Lisbon
    Bonnie Lisbon is one of the troubled Lisbon sisters whose inner life and tragic fate are central to the haunting coming-of-age story in "The Virgin Suicides."
  • E. Myka Bering
    Myka Bering is a meticulous and resourceful Secret Service agent who becomes one of the lead artifact-hunting agents at the mysterious government facility known as Warehouse 13.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4b1e52c8190894281cf7e3283ab completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69cbff210819089900e9a35911f48 completed April 20, 2026, 9:38 p.m.
Created at: April 16, 2026, 11:35 a.m.