Triple

T15043245
Position Surface form Disambiguated ID Type / Status
Subject Harriette E379154 entity
Predicate hasRelatedName P3889 FINISHED
Object Henriette E1038067 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: Henriette | Statement: [Harriette, hasRelatedName, Henriette]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Henriette
Context triple: [Harriette, hasRelatedName, Henriette]
  • A. Henriette
    Henriette is the given first name of the French photographer and painter Dora Maar, renowned for her association with Pablo Picasso and the Surrealist movement.
  • B. Henriette
    Henriette is a cartoon cat character from the Looney Tunes short "Odor-able Kitty," known for being the object of Pepé Le Pew’s misguided romantic pursuits.
  • C. Henriette chosen
    Henriette is a feminine given name of French origin, historically borne by various European women of note.
  • D. Henrietta
    Henrietta is a feminine given name of English origin, historically popular in the 18th and 19th centuries and borne by several notable figures.
  • E. Henrietta
    Henrietta is a suburban community in western New York State, located near Rochester within the Rust Belt region along the Interstate 90 corridor.
  • 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_69d85cd64d108190853797a95c11cc45 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded82f73208190bb55fa6b20074e27 completed April 15, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2ce5d0708190bbfff5d68c5e7a3c completed May 9, 2026, 12:47 p.m.
Created at: April 10, 2026, 3 a.m.