Triple
T3691222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sugar learning platform |
E78346
|
entity |
| Predicate | SugarOnAStickDescription |
P49768
|
FINISHED |
| Object | live USB distribution of Sugar |
—
|
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: live USB distribution of Sugar | Statement: [Sugar learning platform, SugarOnAStickDescription, live USB distribution of Sugar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: SugarOnAStickDescription Context triple: [Sugar learning platform, SugarOnAStickDescription, live USB distribution of Sugar]
-
A.
hasSugarContent
Indicates that one entity possesses or contains a specified amount or level of sugar.
-
B.
traditionalSweet
Indicates that something is a sweet food or dessert prepared according to long-established customs or cultural traditions.
-
C.
isSweeterThan
Indicates that one entity has a higher level of sweetness in taste compared to another entity.
-
D.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
E.
hasSpice
Indicates that one entity contains, includes, or is characterized by a particular spice or set of spices.
- 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_69ad85e285a081908f8cbfa9e2ed9b75 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc4e783a88190b2837a68b8723a25 |
completed | March 8, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69adb84dc5808190850aa6975cb09e27 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb902e61c81908f10494f828e260f |
completed | March 8, 2026, 5:59 p.m. |
Created at: March 8, 2026, 3:26 p.m.