Triple

T3509742
Position Surface form Disambiguated ID Type / Status
Subject Henriette Pressburg E74165 entity
Predicate givenName P17 FINISHED
Object Henriette E211775 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: [Henriette Pressburg, givenName, Henriette]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Henriette
Context triple: [Henriette Pressburg, givenName, Henriette]
  • A. Henriette chosen
    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. Henrietta
    Henrietta is a suburban community in western New York State, located near Rochester within the Rust Belt region along the Interstate 90 corridor.
  • C. Henrietta
    Henrietta is a feminine given name of English origin, historically popular in the 18th and 19th centuries and borne by several notable figures.
  • D. Mariette
    Mariette is a French feminine given name, commonly used as a diminutive or affectionate form of Marie.
  • E. Marie
    Marie is a widely used European given name, especially common in French-speaking countries, derived from the Hebrew name Miryam (Mary).
  • 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc0e1f0c8190b054d9fba16ce4b3 completed March 8, 2026, 6:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69b373e71ae8819096ea39955c92076a completed March 13, 2026, 2:18 a.m.
Created at: March 8, 2026, 3:18 p.m.