Triple
T27748297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hoegaarden |
E702046
|
entity |
| Predicate | beerColorScale |
P99244
|
FINISHED |
| Object | very pale straw |
—
|
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: very pale straw | Statement: [Hoegaarden, beerColorScale, very pale straw]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: beerColorScale Context triple: [Hoegaarden, beerColorScale, very pale straw]
-
A.
beerColor
chosen
Indicates the color characteristic associated with a particular beer.
-
B.
beerStyle
Indicates that one entity is the style or type classification of a beer associated with another entity.
-
C.
alcoholStrengthCategory
Indicates the classification of an alcoholic beverage based on the strength or concentration of its alcohol content.
-
D.
colorScaleSRM
Indicates a relationship where an entity is assigned or characterized by a color scale defined in SRM (Standard Reference Method) units.
-
E.
alcoholByVolumeApprox
Indicates an approximate measurement of the proportion of alcohol by volume contained in a beverage or liquid.
- 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_69ef6a53c7388190899baa6daf42301c |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6371c6454819099f05f09d60a374c |
completed | May 2, 2026, 5:40 p.m. |
| PD | Predicate disambiguation | batch_69f63188e7408190af8ce8b93d128c63 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 4:18 p.m.