Triple

T4300722
Position Surface form Disambiguated ID Type / Status
Subject George Grenville E99829 entity
Predicate givenName P17 FINISHED
Object George E372351 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: George | Statement: [George Grenville, givenName, George]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George
Context triple: [George Grenville, givenName, George]
  • A. George
    George is the heroic protagonist of the fantasy film "The Magic Sword," known for embarking on a perilous quest to rescue a princess from an evil sorcerer.
  • B. George
    George is the first name of George Washington, the first President of the United States and a key leader in the American Revolutionary War.
  • C. George
    George is a town in South Africa’s Western Cape province, known as a gateway to the Garden Route and for its scenic mountains and forests.
  • D. George chosen
    George is a common masculine given name of Greek origin, meaning "farmer" or "earthworker."
  • E. George
    George is a masculine given name of Greek origin meaning "farmer" or "earthworker," widely used in English-speaking and many other cultures.
  • 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_69b345528ebc8190b5abc7e95094792d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3509fb2b88190a13ab88a5b924052 completed March 12, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e4e7a7cc8190a2ffc15c236f80d5 completed March 14, 2026, 10:44 p.m.
Created at: March 12, 2026, 11:08 p.m.