Triple
T15263761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Merge |
E364847
|
entity |
| Predicate | effectOnEnergyUsage |
P7394
|
FINISHED |
| Object | reduced Ethereum energy consumption by over 99 percent |
—
|
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: reduced Ethereum energy consumption by over 99 percent | Statement: [The Merge, effectOnEnergyUsage, reduced Ethereum energy consumption by over 99 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnEnergyUsage Context triple: [The Merge, effectOnEnergyUsage, reduced Ethereum energy consumption by over 99 percent]
-
A.
energyUse
chosen
Indicates the amount or rate at which an entity consumes energy to perform its functions or activities.
-
B.
energyUtilization
Indicates how effectively an entity uses available energy to perform work or sustain its functions.
-
C.
electricityUse
Indicates the amount or pattern of electrical energy consumed by an entity during a specified period or activity.
-
D.
usesEnergyFrom
Indicates that one entity derives or consumes energy originating from another entity as its source.
-
E.
energyContribution
Indicates the amount or role of energy that one entity provides or contributes to another entity, process, or system.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0084fed0481908e452c89cba2be82 |
completed | April 15, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69deca8d1bd48190a4b94f29b425e335 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:14 a.m.