Triple

T5414423
Position Surface form Disambiguated ID Type / Status
Subject Wojcicki E121093 entity
Predicate hasFeminineForm P1613 FINISHED
Object Wojcicka E519386 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: Wojcicka | Statement: [Wojcicki, hasFeminineForm, Wojcicka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wojcicka
Context triple: [Wojcicki, hasFeminineForm, Wojcicka]
  • A. Wójcicki chosen
    Wójcicki is a Polish surname most notably associated with figures such as Susan Wojcicki, the former CEO of YouTube, and her family.
  • B. Walewska
    Walewska is a Polish surname most famously associated with Maria Walewska, a noblewoman known as the mistress of Napoleon Bonaparte.
  • C. Wasilewska
    Wasilewska is a Polish surname most notably associated with Wanda Wasilewska, a 20th-century Polish and Soviet writer and communist activist.
  • D. Radkiewicz
    Radkiewicz is a Polish surname most notably associated with Stanisław Radkiewicz, a prominent communist-era politician and security official in Poland.
  • E. Wojciech
    Wojciech is a masculine given name of Slavic origin, particularly common in Poland.
  • 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_69bd463a41cc8190b32ff5af2b96ca93 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd87bcace08190932fe85e4b4aeffc completed March 20, 2026, 5:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf4121edc4819081fdb79dcc182540 completed March 22, 2026, 1:08 a.m.
Created at: March 20, 2026, 2:05 p.m.