Triple
T33393504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HUC code |
E855111
|
entity |
| Predicate | lowestCommonResolution |
P176849
|
FINISHED |
| Object | 12-digit HUC |
—
|
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: 12-digit HUC | Statement: [HUC code, lowestCommonResolution, 12-digit HUC]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lowestCommonResolution Context triple: [HUC code, lowestCommonResolution, 12-digit HUC]
-
A.
mainResolution
Indicates that one resolution is the primary or most important resolution associated with a given context or entity.
-
B.
typicalResolution
Indicates the usual or standard level of detail or clarity at which something (such as an image, display, or representation) is normally rendered or presented.
-
C.
maximumResolution
Indicates the highest level of detail or fineness at which something (such as an image, display, or measurement) can be represented or processed.
-
D.
lowestOrder
Indicates that one entity has the smallest or minimal order, rank, or priority relative to a set of comparable entities.
-
E.
typicalInputResolution
Indicates the usual or standard resolution at which input is expected or typically processed.
- 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_69f3496e3f1c8190bcecfa82aa9d17ff |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f38159d08190980ad639e08f00f4 |
completed | May 3, 2026, 7:04 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d7bee48190b94e0beb48a1d7fa |
completed | May 3, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69f6f37f36ac8190b1bff8711d6771cb |
completed | May 3, 2026, 7:04 a.m. |
Created at: May 1, 2026, 1:35 a.m.