Triple
T21908951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gorkhaland statehood movement |
E541012
|
entity |
| Predicate | hasRegion |
P285
|
FINISHED |
| Object | Kurseong |
—
|
NE NERFINISHED |
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: Kurseong | Statement: [Gorkhaland statehood movement, hasRegion, Kurseong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kurseong Context triple: [Gorkhaland statehood movement, hasRegion, Kurseong]
-
A.
Kurseong
chosen
Kurseong is a small hill town in the Darjeeling district of northern West Bengal, India, known for its tea gardens, cool climate, and views of the Eastern Himalayas.
-
B.
Jeongeup
Jeongeup is a city in South Korea known for its location in North Jeolla Province and its cultural and historical heritage.
-
C.
Hongseong
Hongseong is a town in South Korea that serves as the administrative capital of South Chungcheong Province.
-
D.
Mokpo
Mokpo is a coastal city in South Jeolla Province, South Korea, known as a regional transportation hub and gateway to numerous nearby islands.
-
E.
Seongsan-eup
Seongsan-eup is a coastal town on South Korea’s Jeju Island known for its scenic landscapes and proximity to the volcanic tuff cone Seongsan Ilchulbong, a UNESCO World Heritage site.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c47b4e8c81908c8076eaa4c8e4f2 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f121d8c3108190a178ec6b3857da3f |
completed | April 28, 2026, 9:08 p.m. |
Created at: April 16, 2026, 7:39 p.m.