Triple
T30721303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thái Nguyên tea |
E782160
|
entity |
| Predicate | hasBrewColor |
P111949
|
FINISHED |
| Object | yellowish green liquor |
—
|
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: yellowish green liquor | Statement: [Thái Nguyên tea, hasBrewColor, yellowish green liquor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBrewColor Context triple: [Thái Nguyên tea, hasBrewColor, yellowish green liquor]
-
A.
beverageColor
Indicates the color or visual hue associated with a given beverage.
-
B.
brewedUsing
Indicates that one entity was produced or prepared by using another entity as an ingredient, material, or component in a brewing process.
-
C.
typicalInfusionColor
chosen
Indicates the usual or characteristic color of a liquid infusion produced from a substance.
-
D.
brewedAccordingTo
Indicates that something has been produced or prepared following a specified brewing method, recipe, or standard.
-
E.
hasBottleColor
Indicates that an entity is associated with a bottle characterized by a specific color.
- 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_69f224acd24481908ed5f96f0d69b5dd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f727afd5d88190ad48735cd1b32787 |
completed | May 3, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_69f72737c42c8190a3f781a5e98868ff |
completed | May 3, 2026, 10:45 a.m. |
Created at: April 29, 2026, 8:36 p.m.