Triple

T10082904
Position Surface form Disambiguated ID Type / Status
Subject Marthe Keller E213946 entity
Predicate familyName P18 FINISHED
Object Keller E412553 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: Keller | Statement: [Marthe Keller, familyName, Keller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Keller
Context triple: [Marthe Keller, familyName, Keller]
  • A. Keller
    Keller is a suburban city in the Dallas–Fort Worth metropolitan area known for its family-friendly neighborhoods and strong public schools.
  • B. Keller chosen
    Keller is the surname of Helen Keller, the renowned American author and disability rights advocate who was both deaf and blind.
  • C. Kelley
    Kelley is a surname most notably associated with Florence Kelley, a prominent American social and political reformer who fought for labor rights and child welfare in the late 19th and early 20th centuries.
  • D. Kahle
    Kahle is a surname most notably associated with Brewster Kahle, the American computer engineer and digital librarian who founded the Internet Archive.
  • E. Kehler
    Kehler is a German-origin surname borne by various individuals, including American Air Force general C. Robert Kehler.
  • 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_69ca839bf730819086900c323c9b8c95 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd04352d081908f676444cd2d2578 completed April 2, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b66b256c8190861066f7c19008d2 completed April 5, 2026, 7:22 p.m.
Created at: March 30, 2026, 9 p.m.