Triple

T6103603
Position Surface form Disambiguated ID Type / Status
Subject Julia Roberts E136062 entity
Predicate notableWork P4 FINISHED
Object Wonder E554427 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: Wonder | Statement: [Julia Roberts, notableWork, Wonder]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wonder
Context triple: [Julia Roberts, notableWork, Wonder]
  • A. Wonder chosen
    Wonder is a 2017 drama film about a boy with a facial difference navigating school and family life, based on R.J. Palacio’s novel of the same name.
  • B. The Wonder
    The Wonder is a psychological period drama film in which Florence Pugh plays an English nurse sent to investigate a young Irish girl who appears to survive without eating.
  • C. The Wonders
    The Wonders are the fictional 1960s pop band from the film "That Thing You Do!", known for their catchy one-hit-wonder title track and Beatles-inspired image.
  • D. Wish
    Wish is an e-commerce platform and mobile shopping app known for offering a wide variety of low-priced goods shipped directly from merchants, primarily in China, to consumers worldwide.
  • E. To the Wonder
    To the Wonder is a 2012 romantic drama film directed by Terrence Malick, noted for its poetic, visually driven storytelling and Emmanuel Lubezki’s lyrical cinematography.
  • 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_69c0087dee9881909e3655be88208c01 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05b3dbc6c8190b9e3d81e6ca9eeb8 completed March 22, 2026, 9:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c12553f1d4819096de40514ef4d2cb completed March 23, 2026, 11:34 a.m.
Created at: March 22, 2026, 4:13 p.m.