Triple
T30542655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Araku Valley |
E777321
|
entity |
| Predicate | coffeeBrandAssociated |
P58563
|
FINISHED |
| Object | Araku Coffee |
—
|
NE NERFINISHED |
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: Araku Coffee | Statement: [Araku Valley, coffeeBrandAssociated, Araku Coffee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coffeeBrandAssociated Context triple: [Araku Valley, coffeeBrandAssociated, Araku Coffee]
-
A.
coffeeBrand
chosen
Indicates that one entity is a brand associated with the production or marketing of coffee products for the other entity.
-
B.
teaBrand
Indicates that one entity is a brand or producer associated with a particular type or product line of tea for the other entity.
-
C.
coffeeOrganization
Indicates a relationship where an organization is involved with coffee, such as producing, distributing, selling, or promoting it.
-
D.
knownBrewer
Indicates that one entity is recognized as the brewer (producer of beer or similar beverages) associated with another entity.
-
E.
coffeeVariety
Indicates a relationship where a specific type or variety of coffee is associated with a coffee-related entity (such as a product, beverage, or plant).
- 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_69f2249d183c8190b79937c1768d2163 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6888c052081909c1117592dac5a59 |
completed | May 2, 2026, 11:28 p.m. |
| PD | Predicate disambiguation | batch_69f67e42d6688190b60e91d2c388c555 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 8:19 p.m.