Triple
T30409112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayou Bonne Idee |
E773560
|
entity |
| Predicate | hasTypicalWaterBodyType |
P92225
|
FINISHED |
| Object | freshwater bayou |
—
|
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: freshwater bayou | Statement: [Bayou Bonne Idee, hasTypicalWaterBodyType, freshwater bayou]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalWaterBodyType Context triple: [Bayou Bonne Idee, hasTypicalWaterBodyType, freshwater bayou]
-
A.
hasBodyOfWaterType
chosen
Indicates that a body of water is classified as being of a particular type or category (such as lake, river, ocean, etc.).
-
B.
hasWaterBodyCharacteristic
Indicates that a water body possesses a specified physical, chemical, or ecological characteristic.
-
C.
locatedInWaterBodyType
Indicates that an entity is situated within or on a body of water of a specified type (e.g., lake, river, ocean).
-
D.
appliesToWaterBody
Indicates that something (such as a rule, condition, property, or effect) is relevant or applicable specifically to a particular water body.
-
E.
hasAreaWaterBody
Indicates that an entity includes, contains, or is associated with a body of water within its area or boundaries.
- 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_69f22490b8b48190ab10c886a8d58c89 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe031bc6208190860099aef72d8dcb |
completed | May 8, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69fe014c8b388190b5d4e0cb95ee2be5 |
completed | May 8, 2026, 3:29 p.m. |
Created at: April 29, 2026, 8:04 p.m.