Triple
T36733877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort Ternan |
E907412
|
entity |
| Predicate | naturalFeatureNearby |
P73654
|
FINISHED |
| Object | tea plantations |
—
|
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: tea plantations | Statement: [Fort Ternan, naturalFeatureNearby, tea plantations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: naturalFeatureNearby Context triple: [Fort Ternan, naturalFeatureNearby, tea plantations]
-
A.
nearGeologicalSite
Indicates that one entity is located in close physical proximity to a geological site or feature.
-
B.
lakeTypeNearby
Indicates that one entity is located near another entity that is classified as a particular type of lake.
-
C.
nearNaturalRegion
chosen
Indicates that one entity is located close to a specified natural region or area in geographic space.
-
D.
followsNaturalFeature
Indicates that one entity’s position, path, or boundary runs alongside or is aligned with a natural geographic feature (such as a river, coastline, or ridgeline).
-
E.
naturalAttractionOf
Indicates a relationship where one entity is a natural feature or site that draws interest, attention, or visitors from another 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_69f76e75aa6881909b844d00a3888ee5 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c9f5a8848190ba956ff27f44e396 |
completed | May 3, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:12 p.m.