Triple

T21304746
Position Surface form Disambiguated ID Type / Status
Subject Marguerite Harrison E525163 entity
Predicate familyName P18 FINISHED
Object Harrison NE NERFINISHED

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: Harrison | Statement: [Marguerite Harrison, familyName, Harrison]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harrison
Context triple: [Marguerite Harrison, familyName, Harrison]
  • A. Harrison chosen
    Harrison is a common English surname borne by numerous notable figures across politics, the arts, and sciences.
  • B. Harrison
    Harrison is a small lakeside city in northern Idaho known for its scenic location on Lake Coeur d'Alene and outdoor recreation opportunities.
  • C. Harrison
    Harrison is a city in New Jersey’s Hudson County, known as a residential and industrial community within the New York metropolitan area.
  • D. Hinkley
    Hinkley is a small unincorporated community in California’s Mojave Desert, best known for the groundwater contamination case made famous by the film "Erin Brockovich."
  • E. Knox
    Knox is a surname most famously associated with Henry Knox, a key American Revolutionary War general and the first United States Secretary of War.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b518b8948190ad69cf9a8784d397 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e75aa341908190963c4368708860b8 completed April 21, 2026, 11:08 a.m.
Created at: April 16, 2026, 4:05 p.m.