Triple

T12569905
Position Surface form Disambiguated ID Type / Status
Subject Saw V E295572 entity
Predicate stars P1956 FINISHED
Object Meagan Good E65940 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: Meagan Good | Statement: [Saw V, stars, Meagan Good]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meagan Good
Context triple: [Saw V, stars, Meagan Good]
  • A. Meagan Good chosen
    Meagan Good is an American actress known for her work in film and television, particularly in romantic comedies and dramas.
  • B. Melonie Diaz
    Melonie Diaz is an American actress known for her work in independent films and television, including prominent roles in projects like "Fruitvale Station" and the "Charmed" reboot.
  • C. Deva Cassel
    Deva Cassel is an Italian model and emerging actress, known as the daughter of Monica Bellucci and Vincent Cassel.
  • D. Lauren Boyle
    Lauren Boyle is a New Zealand freestyle swimmer and multiple World Championship medallist known for her success in middle- and long-distance events.
  • E. Yeardley Smith
    Yeardley Smith is an American actress and voice actress best known for voicing Lisa Simpson on the long-running animated television series "The Simpsons."
  • 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_69d6ad9cac2c81908e8a7bed82d1e21d completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d954a422c88190a22cc34d2eac00ce completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6559336088190874123c06c86630e completed May 2, 2026, 7:50 p.m.
Created at: April 8, 2026, 11:50 p.m.