Triple
T20112658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jenni Rivera |
E490372
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Janney |
—
|
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: Janney | Statement: [Jenni Rivera, givenName, Janney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Janney Context triple: [Jenni Rivera, givenName, Janney]
-
A.
Janney
chosen
Janney is the surname of acclaimed American actress Allison Janney, known for her versatile performances in film, television, and theater.
-
B.
Jenney
Jenney is the surname of William Le Baron Jenney, the American architect often regarded as the father of the modern skyscraper.
-
C.
Payette
Payette is a French-Canadian surname most notably associated with Julie Payette, an engineer, astronaut, and former Governor General of Canada.
-
D.
Considine
Considine is a surname of Irish origin borne by various notable individuals in fields such as politics, entertainment, and sports.
-
E.
Moxey
Moxey is a shy, hapless bricklayer and one of the central members of the group of British migrant workers in the comedy-drama series "Auf Wiedersehen, Pet."
- 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_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e666e21f908190b46c747662ff378a |
completed | April 20, 2026, 5:48 p.m. |
Created at: April 11, 2026, 11:29 p.m.