Triple
T21908751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darjeeling tea |
E541007
|
entity |
| Predicate | monsoonFlushCharacteristics |
P145593
|
FINISHED |
| Object | lower flavor intensity |
—
|
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: lower flavor intensity | Statement: [Darjeeling tea, monsoonFlushCharacteristics, lower flavor intensity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: monsoonFlushCharacteristics Context triple: [Darjeeling tea, monsoonFlushCharacteristics, lower flavor intensity]
-
A.
monsoonDependent
Indicates that the occurrence, intensity, or outcome of something is contingent on or significantly influenced by monsoon conditions.
-
B.
seasonalFlow
Indicates that the flow or intensity of something varies in a recurring pattern according to the seasons.
-
C.
averageWaterDepthDuringMonsoon
Indicates the typical water depth measured over the duration of the monsoon period for a given location or water body.
-
D.
typicalWeatherFeature
Indicates a weather condition or pattern that commonly characterizes a place or time period.
-
E.
wetSeasonAccessibility
Indicates how easily or reliably something can be reached, used, or traversed during the wet or rainy season.
- 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_69e0c47b4e8c81908c8076eaa4c8e4f2 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f121d8c3108190a178ec6b3857da3f |
completed | April 28, 2026, 9:08 p.m. |
| PD | Predicate disambiguation | batch_69e6be9ebf4c8190892df1a8e1313f88 |
completed | April 21, 2026, 12:02 a.m. |
| PDg | Predicate description generation | batch_69e6c187bc548190b4ca13150f6bae38 |
completed | April 21, 2026, 12:15 a.m. |
Created at: April 16, 2026, 7:39 p.m.