Triple

T9330797
Position Surface form Disambiguated ID Type / Status
Subject Tab Hunter E224515 entity
Predicate mother P120 FINISHED
Object Gertrude Gelien E791317 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: Gertrude Gelien | Statement: [Tab Hunter, mother, Gertrude Gelien]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gertrude Gelien
Context triple: [Tab Hunter, mother, Gertrude Gelien]
  • A. Gertrude Gelien chosen
    Gertrude Gelien is the birth name of American actor and 1950s teen idol Tab Hunter.
  • B. Marie de Jongh
    Marie de Jongh was the wife of Sidney Woolf, a British judge and legal figure of the late 19th and early 20th centuries.
  • C. Anna van Gelder
    Anna van Gelder was the wife of famed Dutch admiral Michiel de Ruyter and a member of the Dutch bourgeoisie in the 17th century.
  • D. Johanna Maria van der Haeghen
    Johanna Maria van der Haeghen was a 17th-century Dutch woman best known as the wife of admiral Cornelis Tromp, a prominent naval commander of the Dutch Republic.
  • E. Coosje van Bruggen
    Coosje van Bruggen was a Dutch-American sculptor and art historian best known for her large-scale public art collaborations with her husband Claes Oldenburg.
  • 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_69ca8427a0c08190b749831d5ea98f02 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd37ae4fcc81909be75d51e2dc455d completed April 1, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0e3c30ba88190b192621928136b87 completed April 4, 2026, 10:11 a.m.
Created at: March 30, 2026, 7:39 p.m.