Triple
T19452396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jenji Kohan |
E486644
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jenji |
—
|
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: Jenji | Statement: [Jenji Kohan, givenName, Jenji]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jenji Context triple: [Jenji Kohan, givenName, Jenji]
-
A.
Jenji
chosen
Jenji is the first name of Jenji Kohan, the American television writer and producer best known for creating the series "Weeds" and "Orange Is the New Black."
-
B.
Yeji
Yeji is a town in central Ghana situated on the shores of Lake Volta, known as a local fishing and trading hub.
-
C.
Jeni
Jeni is a common shortened form or nickname for the given name Jennifer.
-
D.
Ji-ah
Ji-ah is a central character in the South Korean coming-of-age film "The World of Us," which explores childhood friendship, loneliness, and social exclusion.
-
E.
Ju-Hee
Ju-Hee is the child of Ji-Yoon Kim, likely a member of a Korean family.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63392aab08190aab09b7c356e5b10 |
completed | April 20, 2026, 2:09 p.m. |
Created at: April 10, 2026, 1:38 p.m.