Triple
T2188083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Columbia South Shore Well Field |
E49796
|
entity |
| Predicate | aquiferType |
P37190
|
FINISHED |
| Object | alluvial aquifer |
—
|
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: alluvial aquifer | Statement: [Columbia South Shore Well Field, aquiferType, alluvial aquifer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aquiferType Context triple: [Columbia South Shore Well Field, aquiferType, alluvial aquifer]
-
A.
hasAquifer
Indicates that one entity possesses, contains, or overlies an aquifer associated with it.
-
B.
reservoirType
Indicates the specific kind or classification of a reservoir associated with an entity.
-
C.
basinType
Indicates the specific kind or classification of a basin associated with an entity (e.g., by form, function, or hydrological role).
-
D.
drainageType
Indicates the kind or classification of drainage associated with or applied to an entity (e.g., how water is removed or flows from it).
-
E.
waterSourceType
Indicates the kind or category of source from which water is obtained.
- F. None of above. chosen
Provenance (4 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_69a88aaba3c48190b351cab9b26989ff |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf9e99f08190892d34485c8f2f25 |
completed | March 7, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69abbda32d1881909d1fd83a751fb21c |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbf9c77fc8190a323bcaf644fb2c5 |
completed | March 7, 2026, 6:03 a.m. |
Created at: March 4, 2026, 7:45 p.m.