Triple
T27119862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marennes-Oléron basin |
E686965
|
entity |
| Predicate | aquacultureType |
P137234
|
FINISHED |
| Object | coastal lagoon farming |
—
|
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: coastal lagoon farming | Statement: [Marennes-Oléron basin, aquacultureType, coastal lagoon farming]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aquacultureType Context triple: [Marennes-Oléron basin, aquacultureType, coastal lagoon farming]
-
A.
aquacultureProduct
Indicates that something is a product derived from aquaculture activities, such as the farming or cultivation of aquatic organisms.
-
B.
aquacultureMethod
chosen
Indicates the method or technique used to cultivate aquatic organisms in controlled water environments.
-
C.
aquacultureAdvantage
Indicates that engaging in aquaculture provides a benefit, improvement, or positive outcome relative to some alternative or baseline.
-
D.
fisheryType
Indicates the specific category or kind of fishery associated with an entity, such as its operational or regulatory classification.
-
E.
fishTypeProduced
Indicates that one entity produces, yields, or is the source of a particular type of fish as an output or product.
- 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_69ef148c2b588190afc15b529f7af845 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f624421d188190a5356a4596df536e |
completed | May 2, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69f61b40f02081909bd9c3ea73249163 |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 8:58 a.m.