Triple
T21537053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bees Make Honey |
E531374
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Ivanno Jeremiah |
—
|
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: Ivanno Jeremiah | Statement: [Bees Make Honey, starring, Ivanno Jeremiah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ivanno Jeremiah Context triple: [Bees Make Honey, starring, Ivanno Jeremiah]
-
A.
Ivanno Jeremiah
chosen
Ivanno Jeremiah is a British actor known for his roles in television series such as "Humans" and "Black Mirror."
-
B.
Daronta Pashayi
Daronta Pashayi is a regional variety of the Pashayi languages spoken in and around the Daronta area of eastern Afghanistan.
-
C.
Jermar Jefferson
Jermar Jefferson is an American football running back best known for his standout collegiate career at Oregon State University and subsequent play in the NFL.
-
D.
Jawan Harris
Jawan Harris is an American R&B singer and songwriter who emerged in the early 2010s with youthful, pop-infused tracks and dance-focused performances.
-
E.
Cavalier Johnson
Cavalier Johnson is an American politician who serves as the mayor of Milwaukee, Wisconsin.
- 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_69e0c45e5b8881908ac18fc2f493b114 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee9d0e5a9c8190894ec3666d3296aa |
completed | April 26, 2026, 11:17 p.m. |
Created at: April 16, 2026, 6:27 p.m.