Triple

T11949988
Position Surface form Disambiguated ID Type / Status
Subject Pippa Passes E284400 entity
Predicate hasCharacter P2308 FINISHED
Object Pippa E956721 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: Pippa | Statement: [Pippa Passes, hasCharacter, Pippa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pippa
Context triple: [Pippa Passes, hasCharacter, Pippa]
  • A. Pippa chosen
    Pippa is the innocent, optimistic young girl at the heart of Robert Browning’s verse drama "Pippa Passes," whose unknowing influence shapes the lives of others.
  • B. Pippa
    Pippa is an English socialite, author, and columnist best known as the younger sister of Catherine, Princess of Wales.
  • C. Jemma Jupe
    Jemma Jupe is a member of the Jupe family, known publicly as a relative of English actor Noah Jupe.
  • D. Penelope Horner
    Penelope Horner was a British actress active in film and television during the mid-20th century, known for her supporting roles in comedies and dramas.
  • E. Tamsin
    Tamsin is a feminine given name of English origin, often associated with actresses and public figures such as Tamsin Egerton.
  • 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_69d6ab2db38c8190b1f0ed6663ef8ada completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90364c2608190a3946c9595c71164 completed April 10, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f471ba7fd88190909596e6e01e8714 completed May 1, 2026, 9:26 a.m.
Created at: April 8, 2026, 9:45 p.m.