Triple
T2506409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Piscataqua River |
E52592
|
entity |
| Predicate | estuaryType |
P15315
|
FINISHED |
| Object | drowned river valley estuary |
—
|
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: drowned river valley estuary | Statement: [Piscataqua River, estuaryType, drowned river valley estuary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estuaryType Context triple: [Piscataqua River, estuaryType, drowned river valley estuary]
-
A.
estuaryName
Indicates the naming relationship that assigns a specific name to an estuary.
-
B.
hasEstuaryType
chosen
Indicates the specific type or classification of an estuary associated with a given water body or location.
-
C.
hasEstuaryNear
Indicates that the estuary of a water body is located in close proximity to a specified place or feature.
-
D.
formsEstuary
Indicates that a river or watercourse meets a larger body of water in such a way that it creates or constitutes an estuary.
-
E.
waterbodyType
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_69ab4958e76481908a235377dd921c9e |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd65d6a988190aaaac8e98540a14f |
completed | March 7, 2026, 7:40 a.m. |
| PD | Predicate disambiguation | batch_69abd0bd996c8190ba8b9d6e4333b8d4 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.