Triple

T13681195
Position Surface form Disambiguated ID Type / Status
Subject Kenny Sailors E328007 entity
Predicate givenName P17 FINISHED
Object Kenneth E561889 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: Kenneth | Statement: [Kenny Sailors, givenName, Kenneth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kenneth
Context triple: [Kenny Sailors, givenName, Kenneth]
  • A. Kenneth
    Kenneth is the formal given name of American country music singer, songwriter, and actor Kenny Rogers.
  • B. Kenneth
    Kenneth is the full given name of American documentary filmmaker Ken Burns, renowned for his in-depth historical films and distinctive storytelling style.
  • C. Kenneth chosen
    Kenneth is a masculine given name of Gaelic origin, commonly used in English-speaking countries.
  • D. Kenneth
    Kenneth is a central male character in the darkly comic stage play "The Woman Who Cooked Her Husband," whose infidelity and subsequent fate drive the plot’s themes of betrayal and revenge.
  • E. Jeffrey
    Jeffrey is a masculine given name of Germanic origin, commonly used in English-speaking countries.
  • 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc66cbb088190907cb89dda8e4ebd completed April 12, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7944347a08190bc1386e78ddb3e71 completed May 3, 2026, 6:30 p.m.
Created at: April 9, 2026, 9:53 p.m.