Triple
T1172198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vumerity |
E24937
|
entity |
| Predicate | foodEffect |
P24603
|
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: [Vumerity, foodEffect, may be taken with or without food]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foodEffect Context triple: [Vumerity, foodEffect, may be taken with or without food]
-
A.
healthEffect
Indicates the impact or consequence that one entity has on the health or well-being of another.
-
B.
foodCustom
Indicates a culturally specific practice, rule, or tradition related to the preparation, serving, or consumption of food.
-
C.
mainFoodAffected
Indicates that a primary or central food item is directly impacted or influenced by a specified action or condition.
-
D.
notableEffect
Indicates that one entity has a significant impact, consequence, or influence on another entity or situation.
-
E.
diet
Indicates that an entity regularly consumes a particular type or range of food as its primary source of nutrition.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bceb3f188190b8b767380fe5986f |
completed | March 1, 2026, 10:25 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5656948190b0b1d5446ad06005 |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bbd7ff1881908c943ecdfea59e81 |
completed | March 1, 2026, 10:21 p.m. |
Created at: March 1, 2026, 7:45 p.m.