Triple
T21473009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | English (Papua New Guinea) |
E529777
|
entity |
| Predicate | spreadFacilitatedBy |
P2899
|
FINISHED |
| Object | education system in Papua New Guinea |
—
|
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: education system in Papua New Guinea | Statement: [English (Papua New Guinea), spreadFacilitatedBy, education system in Papua New Guinea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spreadFacilitatedBy Context triple: [English (Papua New Guinea), spreadFacilitatedBy, education system in Papua New Guinea]
-
A.
spreadBy
chosen
Indicates that something is transmitted, dispersed, or propagated through the agency or action of a specified entity or medium.
-
B.
spreadTo
Indicates that something extends, propagates, or is transmitted from one entity, location, or context to another.
-
C.
sharesUniverseWith
Indicates that two entities exist within the same fictional or narrative universe, implying shared continuity, setting, or canon.
-
D.
sharesLaunchWith
Indicates that two or more entities are launched together in the same launch event or mission.
-
E.
spreadsAs
Indicates that one entity propagates, extends, or disseminates from another entity or source.
- 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_69e0c459acb481909bb6ee452a0045c7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea156dac819087c4594d022d3df6 |
completed | April 23, 2026, 9:44 a.m. |
| PD | Predicate disambiguation | batch_69e631ec1d048190b6da97da8222e413 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:19 p.m.