Triple
T22516674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiger Black |
E556665
|
entity |
| Predicate | alcoholStrength |
P2071
|
FINISHED |
| Object | stronger than Tiger Beer |
—
|
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: stronger than Tiger Beer | Statement: [Tiger Black, alcoholStrength, stronger than Tiger Beer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alcoholStrength Context triple: [Tiger Black, alcoholStrength, stronger than Tiger Beer]
-
A.
alcoholStrengthCategory
Indicates the classification of an alcoholic beverage based on the strength or concentration of its alcohol content.
-
B.
alcoholType
Indicates the specific kind or category of alcohol associated with an entity (e.g., beer, wine, spirits).
-
C.
beerColor
Indicates the color characteristic associated with a particular beer.
-
D.
featuresAlcoholReference
Indicates that the subject includes or contains a reference to alcohol or alcoholic beverages.
-
E.
alcoholLevel
chosen
Indicates the measured concentration or amount of alcohol present in an entity (such as a person, substance, or environment).
- 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_69e11e5657e881909f16ca58352c50da |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15e2df59c81909c4ae2f20f1cbb32 |
completed | April 29, 2026, 1:26 a.m. |
| PD | Predicate disambiguation | batch_69ee625e3b408190a60c759fb0b28fe2 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 16, 2026, 8:50 p.m.