Triple

T3112255
Position Surface form Disambiguated ID Type / Status
Subject Ant-Man and the Wasp E64977 entity
Predicate stars P1956 FINISHED
Object Evangeline Lilly E256908 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: Evangeline Lilly | Statement: [Ant-Man and the Wasp, stars, Evangeline Lilly]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Evangeline Lilly
Context triple: [Ant-Man and the Wasp, stars, Evangeline Lilly]
  • A. Evangeline Lilly chosen
    Evangeline Lilly is a Canadian actress best known for her roles in the television series "Lost" and as Hope van Dyne/The Wasp in the Marvel Cinematic Universe.
  • B. Kate Beckinsale
    Kate Beckinsale is an English actress known for her versatile film career, including prominent roles in action, drama, and comedy films such as the Underworld series and various Hollywood productions.
  • C. Shannon Elizabeth
    Shannon Elizabeth is an American actress and former fashion model best known for her breakout role in the comedy film "American Pie."
  • D. Ali Larter
    Ali Larter is an American actress and former model best known for her roles in films like "Final Destination" and "Legally Blonde" and the TV series "Heroes."
  • E. Teresa Palmer
    Teresa Palmer is an Australian actress known for her roles in films such as "Warm Bodies," "Lights Out," and "Hacksaw Ridge."
  • 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_69ad857eeaf48190b34ebfdaa7a264cf completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada43b0b3c8190a828c9cfcf730ed9 completed March 8, 2026, 4:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20397cbdc8190abdd93b502f9577f completed March 12, 2026, 12:06 a.m.
Created at: March 8, 2026, 3:04 p.m.