Triple

T8114521
Position Surface form Disambiguated ID Type / Status
Subject Susanna Reid E189438 entity
Predicate givenName P17 FINISHED
Object Susanna E364408 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: Susanna | Statement: [Susanna Reid, givenName, Susanna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Susanna
Context triple: [Susanna Reid, givenName, Susanna]
  • A. Susanna
    Susanna is a deuterocanonical addition to the Book of Daniel, telling the story of a virtuous woman falsely accused of adultery and vindicated by the prophet Daniel.
  • B. Susanna chosen
    Susanna is a feminine given name of Hebrew origin, commonly used in various European languages and cultures.
  • C. Susannah
    Susannah is one of the central, romantically entangled characters in Alan Ayckbourn’s comedic stage play "Bedroom Farce."
  • D. Suzanne
    "Suzanne" is a renowned song by Leonard Cohen, celebrated for its poetic lyrics and haunting melody.
  • E. Suzanne
    Suzanne is a central character in Steve Martin’s play "Picasso at the Lapin Agile," representing a young woman entangled romantically with both Picasso and other men in the bohemian Parisian setting.
  • 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_69ca82baad008190ab2859712b9b1607 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb432f2a24819097be6ab9b03567bd completed March 31, 2026, 3:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbea5d39c819099d52545410ae564 completed April 1, 2026, 6:43 a.m.
Created at: March 30, 2026, 5:32 p.m.