Triple
T27307081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Outer Wood Island |
E689090
|
entity |
| Predicate | hasRegionalEconomicActivity |
P114644
|
FINISHED |
| Object | fishing |
—
|
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: fishing | Statement: [Outer Wood Island, hasRegionalEconomicActivity, fishing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionalEconomicActivity Context triple: [Outer Wood Island, hasRegionalEconomicActivity, fishing]
-
A.
regionalEconomyActivity
chosen
Indicates the type or level of economic activity occurring within a specific geographic region.
-
B.
hasEconomicActivity
Indicates that an entity engages in, supports, or is associated with a specific type of economic activity or business operation.
-
C.
hasEconomicActivityLevel
Indicates the degree or intensity of economic activity associated with an entity, such as its level of production, trade, or financial transactions.
-
D.
regionalEconomyType
Indicates the type or classification of an economy associated with a specific region.
-
E.
hasImportantEconomicZoneIn
Indicates that an entity possesses or controls a significant economic zone or area within the specified location.
- 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_69ef355b931c8190a63cafaf7bcc008b |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69fea1f5d8c481908dc3351dc9ecef7f |
completed | May 9, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69fea06b6fe0819095bf4c1bc9809927 |
completed | May 9, 2026, 2:48 a.m. |
Created at: April 27, 2026, 11:25 a.m.