Triple

T8603787
Position Surface form Disambiguated ID Type / Status
Subject Elizabeth Blount E203745 entity
Predicate givenName P17 FINISHED
Object Elizabeth E635861 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: Elizabeth | Statement: [Elizabeth Blount, givenName, Elizabeth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elizabeth
Context triple: [Elizabeth Blount, givenName, Elizabeth]
  • A. Elizabeth
    "Elizabeth" is a popular country and gospel song by The Statler Brothers, known for its rich harmonies and storytelling lyrics.
  • B. Elizabeth chosen
    Elizabeth is the given first name of American silent film actress Betty Bronson, known for her role as Peter Pan in the 1924 film adaptation.
  • C. Elizabeth
    Elizabeth is the central protagonist of the interactive narrative game "If/Then," around whom the story’s key choices and emotional developments revolve.
  • D. Elizabeth
    Elizabeth is the central character in the Broadway musical "If/Then," a woman who explores how a single choice can lead to radically different life paths.
  • E. Elizabeth
    Elizabeth is the given first name of Lady Sarah McCorquodale, the elder sister of Diana, Princess of Wales.
  • 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_69ca832b56948190ba751cec255308f1 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc46dc23448190a5eb63455578427e completed March 31, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea8f8dfa4819080c8ed475a84be41 completed April 2, 2026, 5:35 p.m.
Created at: March 30, 2026, 6:24 p.m.