Triple

T4083917
Position Surface form Disambiguated ID Type / Status
Subject Jean Restout the Younger E87542 entity
Predicate givenName P17 FINISHED
Object Jean E209182 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: Jean | Statement: [Jean Restout the Younger, givenName, Jean]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jean
Context triple: [Jean Restout the Younger, givenName, Jean]
  • A. 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.
  • B. 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.
  • C. Jean chosen
    Jean is a common French given name used for both males and females, equivalent to "John" in English.
  • D. Jean
    Jean is a small unincorporated community in Clark County, Nevada, known primarily as a roadside stop and gateway to Las Vegas for travelers from California.
  • E. Jeanne
    Jeanne was a common French female given name historically borne by notable figures such as queens, saints, and writers.
  • 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_69aed9435cf48190ad1da737c962d19d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefc7a4b488190ab466e2c50329ab3 completed March 9, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b562c9760c8190a9292eb1cea55ab2 completed March 14, 2026, 1:29 p.m.
Created at: March 9, 2026, 3:39 p.m.