Triple

T6357910
Position Surface form Disambiguated ID Type / Status
Subject The Amazing Spider-Man 2 E143037 entity
Predicate starring P1507 FINISHED
Object Felicity Jones E103015 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: Felicity Jones | Statement: [The Amazing Spider-Man 2, starring, Felicity Jones]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Felicity Jones
Context triple: [The Amazing Spider-Man 2, starring, Felicity Jones]
  • A. Felicity Jones chosen
    Felicity Jones is an English actress known for her roles in films such as "The Theory of Everything" and "Rogue One: A Star Wars Story."
  • B. Rebecca Ferguson
    Rebecca Ferguson is a Swedish actress known for her versatile performances in films such as the Mission: Impossible series, The Greatest Showman, and Dune.
  • C. Gemma Arterton
    Gemma Arterton is an English actress known for her roles in films such as "St Trinian's," "Quantum of Solace," and "Prince of Persia: The Sands of Time."
  • D. Kate Fisher
    Kate Fisher is the mother of American singer and actor Eddie Fisher.
  • E. Jessica Henwick
    Jessica Henwick is a British actress known for her roles in genre franchises such as "Game of Thrones," "Star Wars: The Force Awakens," and various action and science fiction films and series.
  • 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_69c008d7a9c4819098d647ec47776917 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c067f5bdd481909cf9db595ddb27df completed March 22, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69c62d5f134c8190817037ad933c4d2b completed March 27, 2026, 7:10 a.m.
Created at: March 22, 2026, 4:32 p.m.