Triple
T22722169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenneth |
E561889
|
entity |
| Predicate | hasFeminineForm |
P1613
|
FINISHED |
| Object | Kenna |
—
|
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: Kenna | Statement: [Kenneth, hasFeminineForm, Kenna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kenna Context triple: [Kenneth, hasFeminineForm, Kenna]
-
A.
Kenna
chosen
Kenna is an Ethiopian-American singer-songwriter and producer known for his genre-blending alternative rock and electronic music, as well as collaborations with prominent artists and producers.
-
B.
Kaela
Kaela is the given name of American professional basketball player Kaela Davis.
-
C.
Kerra
Kerra is a character from the historical fantasy television series "Britannia," set during the Roman invasion of ancient Britain.
-
D.
Keila
Keila is a small town in northern Estonia known for its historic church, scenic Keila River and waterfall, and role as a local administrative and transport hub.
-
E.
Kahanna
Kahanna is an alternative transliteration of the name Kahana, which is used as a personal or place name in various cultural and linguistic contexts.
- 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_69e2454fc984819088213b58ee87a002 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17926ae0c8190af8493cab6b15261 |
completed | April 29, 2026, 3:21 a.m. |
Created at: April 17, 2026, 3:20 p.m.