Triple

T11228614
Position Surface form Disambiguated ID Type / Status
Subject Gemma Chan E265759 entity
Predicate characterPortrayed P1507 FINISHED
Object Sersi E830872 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: Sersi | Statement: [Gemma Chan, characterPortrayed, Sersi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sersi
Context triple: [Gemma Chan, characterPortrayed, Sersi]
  • A. Sersi chosen
    Sersi is a powerful, empathetic Eternal from Marvel Comics and the Marvel Cinematic Universe, known for her matter-transmutation abilities and central role in the Eternals' story.
  • B. Swee'Pea
    Swee'Pea is a baby character from the Popeye franchise, typically portrayed as Popeye's adopted child and often involved in the series' comedic and adventurous situations.
  • C. Tebbe
    Tebbe is a German surname that serves as the etymological root for the name Tibbets.
  • D. Sittas
    Sittas was a prominent Byzantine general and close associate of Emperor Justinian I, noted for his campaigns against the Sassanid Persians and other foes in the early 6th century.
  • E. Fran Fine
    Fran Fine is the flamboyant, fashion-forward, and quick-witted nanny from the 1990s sitcom "The Nanny," known for her distinctive Queens accent and comedic charm.
  • 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e900fbcc8190a3177f8a73564433 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4ad33fdf48190a7118c7c30577ec9 completed April 19, 2026, 10:23 a.m.
Created at: April 8, 2026, 9:30 p.m.