Triple
T26893526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Assam tea |
E677840
|
entity |
| Predicate | colorWhenBrewed |
P111949
|
FINISHED |
| Object | deep amber |
—
|
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: deep amber | Statement: [Assam tea, colorWhenBrewed, deep amber]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorWhenBrewed Context triple: [Assam tea, colorWhenBrewed, deep amber]
-
A.
beverageColor
Indicates the color or visual hue associated with a given beverage.
-
B.
typicalInfusionColor
chosen
Indicates the usual or characteristic color of a liquid infusion produced from a substance.
-
C.
brewedUsing
Indicates that one entity was produced or prepared by using another entity as an ingredient, material, or component in a brewing process.
-
D.
brewedAccordingTo
Indicates that something has been produced or prepared following a specified brewing method, recipe, or standard.
-
E.
coffeeDesignation
Indicates that one entity is designated or classified as a particular type, role, or category of coffee in relation to another entity.
- F. None of above.
Provenance (3 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_69eee9befee48190a26f214faa867be7 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f65aa07c048190a5df30d53d8f0cf5 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 27, 2026, 5:46 a.m.