Triple
T14216585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fisayo Akinade |
E352367
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Cucumber |
E71123
|
NE FINISHED |
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: Cucumber | Statement: [Fisayo Akinade, notableWork, Cucumber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cucumber Context triple: [Fisayo Akinade, notableWork, Cucumber]
-
A.
Cucumber
chosen
Cucumber is a British television drama series created and written by Russell T Davies that explores the lives and relationships of gay men in contemporary Manchester.
-
B.
Cucumber
Cucumber is a widely cultivated vine plant known for its elongated green fruit, commonly eaten fresh in salads or pickled as a vegetable.
-
C.
Aubergine
Aubergine is a poignant stage play by Julia Cho that explores family, grief, and cultural identity through the lens of food and memory.
-
D.
Asparagus
Asparagus is a genus of perennial flowering plants best known for the edible vegetable asparagus spears commonly used in cuisines worldwide.
-
E.
Cucumber Run
Cucumber Run is a small stream in Pennsylvania that feeds the scenic Cucumber Falls in Ohiopyle State Park.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6210213481908fac6893e8a9f143 |
completed | April 14, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d0cb3f88190813542f95ee360bf |
completed | May 8, 2026, 1:31 a.m. |
Created at: April 10, 2026, 1:06 a.m.