Triple

T1856026
Position Surface form Disambiguated ID Type / Status
Subject Victoria Mary Augusta Louise Olga Pauline Claudine Agnes E41703 entity
Predicate givenName P17 FINISHED
Object Pauline E35720 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: Pauline | Statement: [Victoria Mary Augusta Louise Olga Pauline Claudine Agnes, givenName, Pauline]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pauline
Context triple: [Victoria Mary Augusta Louise Olga Pauline Claudine Agnes, givenName, Pauline]
  • A. Pauline chosen
    Pauline is a feminine given name used in various languages, often considered the female form of Paul.
  • B. Paula
    Paula is a feminine given name used in many languages, derived from the Latin name Paulus meaning "small" or "humble."
  • C. Livia Stone
    Livia Stone is the wife of Biz Stone, the co-founder of Twitter and a prominent American entrepreneur.
  • D. Eunice
    Eunice is a feminine given name of Greek origin, commonly associated with women in English-speaking countries.
  • E. Susanna
    Susanna is a deuterocanonical addition to the Book of Daniel, telling the story of a virtuous woman falsely accused of adultery and vindicated by the prophet Daniel.
  • 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_69a8864a83848190a4ec02721306c511 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb07e5ed48190a7b8858e2b355109 completed March 7, 2026, 4:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69add1c89bdc8190acf517a7731fa5c7 completed March 8, 2026, 7:45 p.m.
Created at: March 4, 2026, 7:33 p.m.