Triple

T8240865
Position Surface form Disambiguated ID Type / Status
Subject Cimetière de Passy E192529 entity
Predicate burialPlaceOf P196 FINISHED
Object Pearl White E292883 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: Pearl White | Statement: [Cimetière de Passy, burialPlaceOf, Pearl White]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pearl White
Context triple: [Cimetière de Passy, burialPlaceOf, Pearl White]
  • A. Pearl White chosen
    Pearl White was a pioneering American silent film actress best known as the “Queen of the Serials” for her daring roles in early 20th-century adventure film series.
  • B. Winifred Banks
    Winifred Banks is a suffragette and the mother of the Banks children in the "Mary Poppins" stories and film adaptations.
  • C. Mabel Bianco
    Mabel Bianco is an Argentine physician, feminist activist, and public health expert known for her work on women's reproductive rights and gender equality in health policy.
  • D. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • E. Barbara
    Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
  • 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_69ca82dc8f148190a2c75a98501a7b91 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb783e13648190abf34eb8c244ea17 completed March 31, 2026, 7:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd351871ac81909f8e4a72a6b99ac3 completed April 1, 2026, 3:09 p.m.
Created at: March 30, 2026, 5:47 p.m.