Triple
T2441301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doux |
E53280
|
entity |
| Predicate | hasSugarSource |
P39346
|
FINISHED |
| Object | dosage added after disgorgement |
—
|
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: dosage added after disgorgement | Statement: [Doux, hasSugarSource, dosage added after disgorgement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSugarSource Context triple: [Doux, hasSugarSource, dosage added after disgorgement]
-
A.
hasSugarContent
Indicates that one entity possesses or contains a specified amount or level of sugar.
-
B.
hasMainIngredient
Indicates that one entity is the primary or most significant ingredient used to make another entity.
-
C.
hasSecondarySource
Indicates that an entity is supported, documented, or referenced by a secondary source rather than by a primary or original source.
-
D.
hasAmyloseContent
Indicates that an entity (typically a food or plant material) possesses a specified amount or proportion of amylose in its starch content.
-
E.
isMajorSourceOf
Indicates that one entity serves as a primary or dominant origin, cause, or provider of another entity or effect.
- 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_69ab495b6dac8190ac82661aa1452222 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abcebf7cac8190889e6890d72c256c |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5ac11b081908ce6a506e81a742a |
completed | March 7, 2026, 6:29 a.m. |
| PDg | Predicate description generation | batch_69abcebe7dd08190b197a2a0e78787e3 |
completed | March 7, 2026, 7:07 a.m. |
Created at: March 6, 2026, 9:43 p.m.