Triple

T9490167
Position Surface form Disambiguated ID Type / Status
Subject Rod Keller E228864 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: [Rod Keller, familyName, Keller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Keller
Context triple: [Rod 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_69ca847424f081908180305555139f7a completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd80c6f6bc8190aa09422508bd5d23 completed April 1, 2026, 8:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69d12d202b748190b78e4e972b1ce08d completed April 4, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:55 p.m.