Triple
T4153616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port Tobacco River |
E89964
|
entity |
| Predicate | hasWaterbodyType |
P1011
|
FINISHED |
| Object | estuarine river |
—
|
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: estuarine river | Statement: [Port Tobacco River, hasWaterbodyType, estuarine river]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterbodyType Context triple: [Port Tobacco River, hasWaterbodyType, estuarine river]
-
A.
hasAreaWaterBody
Indicates that an entity includes, contains, or is associated with a body of water within its area or boundaries.
-
B.
appliesToWaterBody
Indicates that something (such as a rule, condition, property, or effect) is relevant or applicable specifically to a particular water body.
-
C.
isInlandWaterBodyOf
Indicates that one water body is an inland (non-oceanic) water feature that is geographically part of, contained within, or associated with another entity.
-
D.
hasWatercourseType
Indicates the specific kind or category of watercourse (such as river, stream, or canal) associated with an entity.
-
E.
waterbodyType
chosen
Indicates the classification of a water body according to its type (e.g., river, lake, ocean, etc.).
- 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_69aed95a59a881909b26e70b42c6811a |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af033ef6648190adde17f943d89c78 |
completed | March 9, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69af018c101081909070da5b11e5eb3d |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:44 p.m.