Triple

T17005277
Position Surface form Disambiguated ID Type / Status
Subject Helen Keller E412553 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: [Helen Keller, familyName, Keller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Keller
Context triple: [Helen Keller, familyName, Keller]
  • A. Keller chosen
    Keller is the surname of Helen Keller, the renowned American author and disability rights advocate who was both deaf and blind.
  • B. Keller
    Keller is a suburban city in the Dallas–Fort Worth metropolitan area known for its family-friendly neighborhoods and strong public schools.
  • C. Krier
    Krier is a surname most notably associated with Leon Krier, a Luxembourgish architect and urban planner known for his advocacy of traditional urbanism and criticism of modernist architecture.
  • D. 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.
  • E. Kahle
    Kahle is a surname most notably associated with Brewster Kahle, the American computer engineer and digital librarian who founded the Internet Archive.
  • 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_69d886cb581c8190ab05f4b429c9cd85 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d382400c819092ec0ca0de815888 completed April 18, 2026, 6:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc2035848190bf299875d37c8ac7 completed May 10, 2026, 7:27 p.m.
Created at: April 10, 2026, 5:32 a.m.