Triple
T7071169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanino Bay |
E164698
|
entity |
| Predicate | importanceForRegion |
P12510
|
FINISHED |
| Object | supports regional employment |
—
|
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: supports regional employment | Statement: [Vanino Bay, importanceForRegion, supports regional employment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: importanceForRegion Context triple: [Vanino Bay, importanceForRegion, supports regional employment]
-
A.
impactRegion
Indicates the geographic or spatial area that is affected or influenced by a particular event, action, or phenomenon.
-
B.
hasRegionalSignificance
chosen
Indicates that something holds particular importance, influence, or relevance within a specific geographic region.
-
C.
influencesRegion
Indicates that one entity has an effect on, shapes, or alters the conditions, characteristics, or behavior of a specified region.
-
D.
mentionsRegion
Indicates that one entity explicitly refers to or cites a specific geographic region in its content or context.
-
E.
relativeImportanceInCountry
Indicates the comparative significance or priority of something within the context of a specific country.
- 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_69c6887b96548190a8a9b3ac8adf4119 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4c862f481908d1faf6ed57774f1 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bfcb948190a5ada74fb8c054cb |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:39 p.m.