Triple

T16780851
Position Surface form Disambiguated ID Type / Status
Subject Rango E407852 entity
Predicate voiceCastMember P9616 FINISHED
Object Abigail Breslin E381331 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: Abigail Breslin | Statement: [Rango, voiceCastMember, Abigail Breslin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abigail Breslin
Context triple: [Rango, voiceCastMember, Abigail Breslin]
  • A. Abigail Breslin chosen
    Abigail Breslin is an American actress who gained prominence as a child star in films like "Little Miss Sunshine" and has continued to work in both film and television.
  • B. Debby Ryan
    Debby Ryan is an American actress and singer best known for her leading roles in Disney Channel series like "Jessie" and films such as "Radio Rebel" and "Insatiable."
  • C. Madelaine Petsch
    Madelaine Petsch is an American actress best known for playing Cheryl Blossom on the television series "Riverdale."
  • D. Chloë Grace Moretz
    Chloë Grace Moretz is an American actress known for her versatile performances in films such as "Kick-Ass," "Let Me In," and "If I Stay."
  • E. Dakota Fanning
    Dakota Fanning is an American actress who rose to fame as a child star in films like "I Am Sam" and has since built a diverse career in both mainstream and independent cinema.
  • 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_69d8839270588190886720d9519bbf8f completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b216726881908ddc9cdc772cd5e4 completed April 18, 2026, 4:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00ab0300e48190ad088cd11098ca34 completed May 10, 2026, 3:57 p.m.
Created at: April 10, 2026, 5:22 a.m.