Triple

T22494391
Position Surface form Disambiguated ID Type / Status
Subject Kenneth Lauren Burns E556100 entity
Predicate givenName P17 FINISHED
Object Kenneth NE NERFINISHED

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: [Kenneth Lauren Burns, givenName, Kenneth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kenneth
Context triple: [Kenneth Lauren Burns, givenName, Kenneth]
  • A. Kenneth
    Kenneth is the formal given name of American country music singer, songwriter, and actor Kenny Rogers.
  • B. Kenneth chosen
    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
    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 (2 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_69e11e5445bc8190b6a9481926db3355 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15cb0dfb88190a4175e5e95d7ad4b completed April 29, 2026, 1:19 a.m.
Created at: April 16, 2026, 8:49 p.m.