Triple
T16946213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sovaldi |
E411074
|
entity |
| Predicate | takenWithFood |
P68666
|
FINISHED |
| Object | may be taken with or without food |
—
|
LITERAL 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: may be taken with or without food | Statement: [Sovaldi, takenWithFood, may be taken with or without food]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: takenWithFood Context triple: [Sovaldi, takenWithFood, may be taken with or without food]
-
A.
usesFood
Indicates that one entity employs or consumes a food item as a resource, ingredient, or means to achieve some purpose.
-
B.
administrationWithFood
chosen
Indicates that a substance (such as a medication) is to be taken together with food or during a meal.
-
C.
isTypicallyConsumedFrom
Indicates that one entity is most commonly eaten or drunk using, contained in, or taken from the other entity.
-
D.
eatenAs
Indicates that one entity is consumed or used as food by another entity.
-
E.
يتناول
Indicates that an entity is consuming or taking something, such as food, drink, or medicine.
- F. None of above.
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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cfb25e0c8190948e62d9575ae9cd |
completed | April 18, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_69e32b9aa8748190b248890aca86753d |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:31 a.m.