Triple

T7604123
Position Surface form Disambiguated ID Type / Status
Subject The Princess Diaries 2: Royal Engagement E180056 entity
Predicate editedBy P1954 FINISHED
Object Bruce Green E286424 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: Bruce Green | Statement: [The Princess Diaries 2: Royal Engagement, editedBy, Bruce Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bruce Green
Context triple: [The Princess Diaries 2: Royal Engagement, editedBy, Bruce Green]
  • A. Bruce Green chosen
    Bruce Green is a film editor known for his work on feature films including the 1995 drama "The Basketball Diaries."
  • B. Scott Green
    Scott Green is an American higher-education administrator and business executive who serves as president of the University of Idaho.
  • C. Scott Green
    Scott Green is a former National Football League official best known for serving as a referee in multiple Super Bowls.
  • D. Benjamin Green
    Benjamin Green was a 19th-century British architect best known for designing prominent public monuments and buildings in northern England.
  • E. Mark Greene
    Mark Greene is a central fictional emergency physician and one of the original main characters on the television series "ER."
  • 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_69c69f3567008190ab01d2ca7b53584a completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f9fbd1408190b721bf016f997c7b completed March 27, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8684f3cf08190bc3cbafbd8c1b9a0 completed March 28, 2026, 11:46 p.m.
Created at: March 27, 2026, 3:54 p.m.