Triple
T17077334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgia Café au Lait |
E414382
|
entity |
| Predicate | hasDairyContent |
P125779
|
FINISHED |
| Object | contains milk |
—
|
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: contains milk | Statement: [Georgia Café au Lait, hasDairyContent, contains milk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDairyContent Context triple: [Georgia Café au Lait, hasDairyContent, contains milk]
-
A.
isDairyFree
Indicates that something does not contain dairy ingredients or components derived from milk.
-
B.
lactoseContent
Indicates the amount or presence of lactose contained within a given substance or product.
-
C.
hasNutrientContent
Indicates that one entity contains or provides a specified amount or type of nutrient relative to another entity or standard.
-
D.
isAllergenFor
Indicates that one entity acts as an allergen that can trigger an allergic reaction in another entity.
-
E.
milkComposition
Indicates the specific nutrients and components that make up a given sample of milk.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbc625c48190b679a521180e10ad |
completed | April 18, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69e35d642f74819098c014135e249b27 |
completed | April 18, 2026, 10:31 a.m. |
| PDg | Predicate description generation | batch_69e3753f93c88190808fec5692f66699 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:34 a.m.