Triple
T20301212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Farxiga |
E505482
|
entity |
| Predicate | takenWithOrWithoutFood |
P139585
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Farxiga, takenWithOrWithoutFood, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: takenWithOrWithoutFood Context triple: [Farxiga, takenWithOrWithoutFood, true]
-
A.
isTypicallyConsumedFrom
Indicates that one entity is most commonly eaten or drunk using, contained in, or taken from the other entity.
-
B.
usesFood
Indicates that one entity employs or consumes a food item as a resource, ingredient, or means to achieve some purpose.
-
C.
administrationWithFood
Indicates that a substance (such as a medication) is to be taken together with food or during a meal.
-
D.
eatingPermitted
Indicates that an entity is allowed or authorized to eat in a given context or situation.
-
E.
hasFoodOrDrink
Indicates that an entity possesses, provides, or is associated with some type of food or drink.
- F. None of above. chosen
Provenance (4 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_69e0b4b8ab648190906e18538c250148 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6770c700c81909da247cef0d0f1eb |
completed | April 20, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69e55b21b09081909e46691b6f45a07f |
completed | April 19, 2026, 10:45 p.m. |
| PDg | Predicate description generation | batch_69e56702ad04819099c1c08f28d16809 |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 16, 2026, 11:17 a.m.