Triple
T99467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Keene, New York |
E2007
|
entity |
| Predicate | geographyFeature |
P1094
|
FINISHED |
| Object | mountainous terrain |
—
|
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: mountainous terrain | Statement: [Town of Keene, New York, geographyFeature, mountainous terrain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographyFeature Context triple: [Town of Keene, New York, geographyFeature, mountainous terrain]
-
A.
hasNaturalFeature
chosen
Indicates that one entity possesses, contains, or is characterized by a particular natural feature (such as a mountain, river, forest, or coastline).
-
B.
hasLandform
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
C.
drainageBasin
Indicates the area of land where all precipitation and surface water flow are collected and drained toward a particular river, lake, or other water body.
-
D.
physiographicDivisionOf
Indicates that one geographic area is a sub-region or component within the larger physiographic division of another area.
-
E.
geographicCenter
Indicates the location that serves as the central point of a geographic area or region.
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a253b95d4c81909d1f2bc37e799c44 |
completed | Feb. 28, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69a24ebfc5a88190bdd1653b9fa541fe |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.