Triple

T2690759
Position Surface form Disambiguated ID Type / Status
Subject Vera Rubin E58395 entity
Predicate givenName P17 FINISHED
Object Vera E58395 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: Vera | Statement: [Vera Rubin, givenName, Vera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vera
Context triple: [Vera Rubin, givenName, Vera]
  • A. Vera
    Vera is a memorable supporting character from the 1989 Eddie Murphy film "Harlem Nights," known for her tough, comedic persona.
  • B. Vera chosen
    Vera Rubin was an influential American astronomer whose pioneering work on galaxy rotation curves provided key evidence for the existence of dark matter.
  • C. Veronika
    Veronika is the troubled young protagonist of Paulo Coelho's novel "Veronika Decides to Die," whose suicide attempt leads her to a transformative stay in a mental institution.
  • D. Vera Boldis
    Vera Boldis is best known as the former wife of Dee Dee Ramone, the bassist and songwriter of the pioneering punk rock band the Ramones.
  • E. Aloysya
    Aloysya is a given name, typically a feminine variant of Aloysius, used in various cultures and languages.
  • 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_69ab4ac269e481909cb317d79e68b75b completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda0cb9b48190ab354c277cef9e23 completed March 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf61b83c8190ab254d927cb908f2 completed March 10, 2026, 5:42 a.m.
Created at: March 6, 2026, 9:54 p.m.