Triple

T15909576
Position Surface form Disambiguated ID Type / Status
Subject Lacey Chabert E385809 entity
Predicate birthName P65 FINISHED
Object Lacey Nicole Chabert E141138 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: Lacey Nicole Chabert | Statement: [Lacey Chabert, birthName, Lacey Nicole Chabert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lacey Nicole Chabert
Context triple: [Lacey Chabert, birthName, Lacey Nicole Chabert]
  • A. Lacey Chabert chosen
    Lacey Chabert is an American actress and voice actress best known for her roles in the film "Mean Girls," numerous Hallmark Channel movies, and early voice work in animated series.
  • B. Jessica Lucas
    Jessica Lucas is a Canadian actress known for her roles in film and television, including prominent appearances in projects like the monster movie "Cloverfield."
  • C. Madelaine Petsch
    Madelaine Petsch is an American actress best known for playing Cheryl Blossom on the television series "Riverdale."
  • D. Amber Tamblyn
    Amber Tamblyn is an American actress and writer best known for her roles in the television series "Joan of Arcadia" and films such as "The Sisterhood of the Traveling Pants."
  • E. Kyliegh Curran
    Kyliegh Curran is an American actress best known for her roles in the horror film "Doctor Sleep" and the Netflix series "The Fall of the House of Usher."
  • 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_69d86da686e4819097cbf3b1fc2d881d completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1565ea7a8819097efffda366b5245 completed April 16, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0025ec39a8819081c0cf996bc59416 completed May 10, 2026, 6:30 a.m.
Created at: April 10, 2026, 4:52 a.m.