Triple
T15791287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pareto |
E382866
|
entity |
| Predicate | hasDerivedConcept |
P909
|
FINISHED |
| Object | Pareto principle |
E382867
|
NE FINISHED |
How this triple was built (3 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: Pareto principle | Statement: [Pareto, hasDerivedConcept, Pareto principle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pareto principle Context triple: [Pareto, hasDerivedConcept, Pareto principle]
-
A.
Pareto principle
chosen
The Pareto principle is an economic and management concept stating that roughly 80% of effects come from 20% of causes, often used to prioritize efforts and resources.
-
B.
Pareto efficiency
Pareto efficiency is an economic concept describing an allocation of resources where no individual can be made better off without making someone else worse off.
-
C.
Pareto
Pareto is an Italian surname most famously associated with economist and sociologist Vilfredo Pareto, whose work led to the Pareto principle (the 80/20 rule).
-
D.
Lusser's law
Lusser's law is a reliability engineering principle that states the overall reliability of a system is the product of the reliabilities of its individual components, highlighting how system reliability decreases as more components are added in series.
-
E.
Zipf's law
Zipf's law is an empirical statistical principle observing that in many datasets, such as word frequencies in natural language, the frequency of an item is inversely proportional to its rank in a frequency table.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDerivedConcept Context triple: [Pareto, hasDerivedConcept, Pareto principle]
-
A.
hasSubConcept
Indicates that one concept is a more specific, subordinate, or narrower idea within the scope of another, more general concept.
-
B.
derivedFrom
chosen
Indicates that one entity originates, is obtained, or is developed from another source entity.
-
C.
hasConcept
Indicates that an entity includes, embodies, or is associated with a particular concept.
-
D.
hasConceptualOrigin
Indicates that something conceptually originates from, is derived from, or is fundamentally based on another thing.
-
E.
derivedBy
Indicates that one entity is obtained, produced, or inferred from another through some transformation, process, or reasoning.
- F. None of above.
Provenance (4 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d819c881908bc43a6124a1bb2e |
completed | April 16, 2026, 10:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff998981088190b9ce9d99c0481e21 |
completed | May 9, 2026, 8:31 p.m. |
| PD | Predicate disambiguation | batch_69e00537bd1c81908d6e832792fd934f |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:48 a.m.