Triple
T6040927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Land of a Thousand Hills |
E134540
|
entity |
| Predicate | geographicalFeatureCount |
P52634
|
FINISHED |
| Object | many hills |
—
|
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: many hills | Statement: [Land of a Thousand Hills, geographicalFeatureCount, many hills]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographicalFeatureCount Context triple: [Land of a Thousand Hills, geographicalFeatureCount, many hills]
-
A.
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.
-
B.
geographicalNature
chosen
Indicates the natural geographic characteristics or physical landscape type associated with a place or region.
-
C.
hasNumberOfRivers
Indicates the quantitative relationship specifying how many rivers are associated with a given entity.
-
D.
hasNumberOfInhabitedIslands
Indicates the relationship that specifies how many islands within a given area or jurisdiction are inhabited.
-
E.
hasNumberOfMajorIslands
Indicates the quantitative relationship specifying how many major islands are associated with a given entity.
- 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_69c00875db5c819099dd5bb833ec43c2 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056cf82d481909d5161fe3643e7ed |
completed | March 22, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69c049eb52a08190ac10fd703735f5aa |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:08 p.m.