Triple

T7100044
Position Surface form Disambiguated ID Type / Status
Subject Harold Rupert Leofric George Alexander E165432 entity
Predicate givenName P17 FINISHED
Object Rupert E74177 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: Rupert | Statement: [Harold Rupert Leofric George Alexander, givenName, Rupert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rupert
Context triple: [Harold Rupert Leofric George Alexander, givenName, Rupert]
  • A. Rupert chosen
    Rupert is a masculine given name of Germanic origin, commonly used in English-speaking countries and borne by various notable figures.
  • B. Rupert
    Rupert is a small town located in Greenbrier County in the state of West Virginia, United States.
  • C. Rupert Griffin
    Rupert Griffin is known primarily as the brother of American actress and 1950s film star Debra Paget.
  • D. Rupert Macabee
    Rupert Macabee is a character in the 1957 Charlie Chaplin film "A King in New York," appearing in its satirical portrayal of politics and media in postwar America.
  • E. Reginald
    Reginald is a masculine given name of English origin that has been borne by various notable figures, including military officers, politicians, and artists.
  • 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_69c6887fcddc8190a5d58908f6dee590 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e58531c88190a32746f9a97da709 completed March 27, 2026, 8:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c79ca6236c81908a7051bd00d0ca90 completed March 28, 2026, 9:17 a.m.
Created at: March 27, 2026, 2:42 p.m.