Triple

T5599469
Position Surface form Disambiguated ID Type / Status
Subject George Senesky E147079 entity
Predicate givenName P17 FINISHED
Object George unclear NED1 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 Senesky, givenName, George]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George
Context triple: [George Senesky, givenName, George]
  • A. 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.
  • B. 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.
  • C. George
    George is one of the central child detectives in Enid Blyton’s classic Secret Seven mystery series.
  • D. George
    George is the given name of George Washington Vanderbilt II, the American art collector and member of the prominent Vanderbilt family who built the Biltmore Estate.
  • E. George
    George is the birth name of the legendary American baseball player Babe Ruth, one of the sport’s most iconic figures.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69c009043d648190a7af89698ccf1e3e completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020d936dc8190a2e599f1df9fdd91 completed March 22, 2026, 5:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69c027ee724c819086b92ea127961e09 completed March 22, 2026, 5:33 p.m.
Created at: March 22, 2026, 3:38 p.m.