Triple
T22488457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | poutine râpée |
E555950
|
entity |
| Predicate | hasCaloricDensity |
P99243
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [poutine râpée, hasCaloricDensity, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCaloricDensity Context triple: [poutine râpée, hasCaloricDensity, high]
-
A.
hasCalories
Indicates that an entity contains a specified amount of caloric energy.
-
B.
calorieProfile
Indicates the relationship between an entity and the detailed breakdown of its caloric characteristics, such as total calories and their distribution.
-
C.
calorieLevel
chosen
Indicates the relationship between an entity and the amount of calories it contains or provides, typically categorized by intensity or range (e.g., low, medium, high).
-
D.
hasNutrientContent
Indicates that one entity contains or provides a specified amount or type of nutrient relative to another entity or standard.
-
E.
hasMeanDensity
Indicates that one entity possesses a specified average mass per unit volume (mean density).
- 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_69e11e53897c819088863779f8c50bb0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15c3e73108190be5ca89ea96a85e4 |
completed | April 29, 2026, 1:17 a.m. |
| PD | Predicate disambiguation | batch_69e898b6eee08190ba673a0ee329e671 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:49 p.m.