Triple
T19288153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sonya Walger |
E482367
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Caffeine |
—
|
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: Caffeine | Statement: [Sonya Walger, notableWork, Caffeine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caffeine Context triple: [Sonya Walger, notableWork, Caffeine]
-
A.
Caffeine
chosen
"Caffeine" is a young adult novel by Sharon Robinson that explores themes of adolescence, family, and personal struggle.
-
B.
Coffee
"Coffee" is a song by the American singer-songwriter Miguel, known for its smooth blend of R&B and sensual, atmospheric production.
-
C.
Coffee
Coffee is a popular brewed beverage made from roasted coffee beans, known for its stimulating caffeine content and rich, diverse flavors.
-
D.
Black Caffeine
"Black Caffeine" is a song featured on the country album *Old Yellow Moon* by Emmylou Harris and Rodney Crowell.
-
E.
Coca
Coca is a small city in Ecuador that serves as a key gateway to the Amazon rainforest and regional oil operations.
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc043fa481909bbe281a70fb508e |
completed | April 20, 2026, 10:12 a.m. |
Created at: April 10, 2026, 1:30 p.m.