Triple
T8744582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coal Pits Wash |
E207791
|
entity |
| Predicate | geographicalFeatureType |
P80940
|
FINISHED |
| Object | intermittent stream |
—
|
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: intermittent stream | Statement: [Coal Pits Wash, geographicalFeatureType, intermittent stream]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographicalFeatureType Context triple: [Coal Pits Wash, geographicalFeatureType, intermittent stream]
-
A.
geographicalNature
Indicates the natural geographic characteristics or physical landscape type associated with a place or region.
-
B.
refersToGeographicFeature
Indicates that one entity makes reference to, denotes, or is associated with a specific geographic feature such as a landform, body of water, or other physical location.
-
C.
topographicalCategory
chosen
Indicates the type of landform or surface feature that characterizes the physical terrain associated with an entity.
-
D.
landerType
Indicates the specific kind or category of lander involved in the relationship or action.
-
E.
GNISFeatureClass
Indicates the categorical type or class assigned to a geographic feature in the Geographic Names Information System (GNIS).
- 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_69ca835bb2bc819084bb5906cb6ef7f8 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d72e47c819099540d062d35ebd5 |
completed | March 31, 2026, 11:49 p.m. |
| PD | Predicate disambiguation | batch_69cc5c160dac8190b4aeb4bf0529de52 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:38 p.m.