Triple
T30274914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quinchía |
E769909
|
entity |
| Predicate | belongsToCoffeeAxis |
P86858
|
FINISHED |
| Object | Eje Cafetero |
—
|
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: Eje Cafetero | Statement: [Quinchía, belongsToCoffeeAxis, Eje Cafetero]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToCoffeeAxis Context triple: [Quinchía, belongsToCoffeeAxis, Eje Cafetero]
-
A.
belongsToCup
Indicates that something is a component, content, or attribute of a specific cup, showing that it is associated with or contained by that cup.
-
B.
coffeeOrganization
Indicates a relationship where an organization is involved with coffee, such as producing, distributing, selling, or promoting it.
-
C.
partOfCoffeeRegion
chosen
Indicates that one entity is a subregion or component area within a larger coffee-producing region.
-
D.
coffeeDesignationType
Indicates the specific classification or type designation assigned to a coffee (e.g., by quality, origin, or regulatory category).
-
E.
hasCaffeinatedOption
Indicates that something offers or includes at least one option that contains caffeine.
- 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_69f224856d9881908c7f0dd64f059672 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fdee770af48190aca2670db50f8b49 |
completed | May 8, 2026, 2:08 p.m. |
| PD | Predicate disambiguation | batch_69fdecec98a08190a357d816dc2a6dbe |
completed | May 8, 2026, 2:02 p.m. |
Created at: April 29, 2026, 7:44 p.m.