Triple
T21311417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jenna Lazenby |
E525344
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jenna |
—
|
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: Jenna | Statement: [Jenna Lazenby, givenName, Jenna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jenna Context triple: [Jenna Lazenby, givenName, Jenna]
-
A.
Jenna
chosen
Jenna is a common feminine given name, often used as a diminutive or variant of Jennifer.
-
B.
Jenna
Jenna is a central character in the 2006 romantic drama film "The Last Kiss," serving as the protagonist's pregnant girlfriend whose relationship turmoil drives much of the story's emotional conflict.
-
C.
Jenna Russell
Jenna Russell is an acclaimed British actress and singer, particularly known for her work in West End musical theatre and award-winning performances.
-
D.
Jenna York
Jenna York is a member of the York family, known for their ownership and leadership of the NFL’s San Francisco 49ers franchise.
-
E.
Jenna Boyd
Jenna Boyd is an American actress best known for her roles in films like "The Missing" and the Netflix series "Atypical."
- 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_69e0b518b8948190ad69cf9a8784d397 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e75dc926c881909d70a317070ef295 |
completed | April 21, 2026, 11:21 a.m. |
Created at: April 16, 2026, 4:17 p.m.