Triple
T326109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nobel Prize laureates |
E6521
|
entity |
| Predicate | haveGlobalDiversity |
P1381
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Nobel Prize laureates, haveGlobalDiversity, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveGlobalDiversity Context triple: [Nobel Prize laureates, haveGlobalDiversity, true]
-
A.
hasDiverseLandscape
Indicates that an entity possesses a variety of distinct physical or environmental features within its geographic area.
-
B.
hasGlobalReach
chosen
Indicates that an entity’s influence, operations, or impact extends across multiple countries or worldwide.
-
C.
hasGlobalPlan
Indicates that an entity possesses or is associated with an overarching, comprehensive plan that applies at a global or system-wide level.
-
D.
hasEndemicSpecies
Indicates that a place or region contains species that are native to and found only within that specific geographic area.
-
E.
hasEndemismLevel
Indicates the degree to which something is restricted or native to a particular geographic area or region.
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eb1a37c08190b1380f6bf8513a37 |
completed | Feb. 28, 2026, 1:18 p.m. |
| PD | Predicate disambiguation | batch_69a2e949364c8190bc2351f5413f5057 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.