Triple
T4389285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RP-1 |
E99321
|
entity |
| Predicate | containsAdditives |
P56320
|
FINISHED |
| Object | antioxidants |
—
|
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: antioxidants | Statement: [RP-1, containsAdditives, antioxidants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsAdditives Context triple: [RP-1, containsAdditives, antioxidants]
-
A.
hasSugarFreeVariant
Indicates that an item has a corresponding version or option that is formulated without sugar.
-
B.
isSugarFree
Indicates that something does not contain sugar or has been formulated without added sugar.
-
C.
containsAllergenicCompound
Indicates that the subject entity includes one or more compounds known to cause allergic reactions.
-
D.
ingredientType
Indicates that one entity is classified as a specific type or category of ingredient in relation to another.
-
E.
traditionallyBelievedToContain
Indicates that something is customarily or historically thought to include or hold something else, regardless of whether this belief is factually accurate.
- 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_69b3454f739481909ff6c28331f0c0b9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35281900c8190882e9ccfa44ab86f |
completed | March 12, 2026, 11:55 p.m. |
| PD | Predicate disambiguation | batch_69b34f572efc8190bad1e5078cbcb75a |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b3501834448190bedf775a80da4778 |
completed | March 12, 2026, 11:45 p.m. |
Created at: March 12, 2026, 11:19 p.m.