Triple

T9709358
Position Surface form Disambiguated ID Type / Status
Subject Jeanne Rucar E234981 entity
Predicate givenName P17 FINISHED
Object Jeanne E191141 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: Jeanne | Statement: [Jeanne Rucar, givenName, Jeanne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeanne
Context triple: [Jeanne Rucar, givenName, Jeanne]
  • A. Jeanne chosen
    Jeanne was a common French female given name historically borne by notable figures such as queens, saints, and writers.
  • B. Renée
    Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
  • C. Jeanne Carmen
    Jeanne Carmen was an American model, pin-up girl, and B-movie actress known for her roles in low-budget films of the 1950s and her colorful Hollywood social life.
  • D. Jean
    Jean is a given name associated here with Georges Cuvier, the influential French naturalist and zoologist who founded the field of comparative anatomy and helped establish extinction as a scientific fact.
  • E. Jean
    Jean is the given first name of Henry Dunant, the Swiss humanitarian who founded the Red Cross and received the first Nobel Peace Prize.
  • 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_69ca84cd8fa0819090a5e243ceb37003 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9da7c6188190b086f7e411378268 completed April 1, 2026, 10:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19f8476e08190865700679069dee6 completed April 4, 2026, 11:32 p.m.
Created at: March 30, 2026, 8:19 p.m.