Triple
T8716562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Bismarck Plate |
E206907
|
entity |
| Predicate | hasRegionalImpactOn |
P19397
|
FINISHED |
| Object | Papua New Guinea tectonics |
—
|
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: Papua New Guinea tectonics | Statement: [North Bismarck Plate, hasRegionalImpactOn, Papua New Guinea tectonics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionalImpactOn Context triple: [North Bismarck Plate, hasRegionalImpactOn, Papua New Guinea tectonics]
-
A.
impactRegion
Indicates the geographic or spatial area that is affected or influenced by a particular event, action, or phenomenon.
-
B.
hasRegionalInfluenceFrom
Indicates that one entity’s influence, impact, or authority in a region is derived from or shaped by another entity.
-
C.
hasRegionalSignificance
Indicates that something holds particular importance, influence, or relevance within a specific geographic region.
-
D.
nationalImpact
Indicates that something has a significant effect or influence at the level of an entire nation.
-
E.
influencesRegion
chosen
Indicates that one entity has an effect on, shapes, or alters the conditions, characteristics, or behavior of a specified 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_69ca83572d4881909bef3be2b578d539 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5cd9c2a08190a65ab0ce573153d2 |
completed | March 31, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69cc456e806c819087e7d66ee737f242 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:36 p.m.