Triple
T7015388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darjeeling Himalayan Railway |
E162687
|
entity |
| Predicate | notableStop |
P3858
|
FINISHED |
| Object | Kurseong |
E302365
|
NE 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: Kurseong | Statement: [Darjeeling Himalayan Railway, notableStop, Kurseong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kurseong Context triple: [Darjeeling Himalayan Railway, notableStop, 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.
Hongseong
Hongseong is a town in South Korea that serves as the administrative capital of South Chungcheong Province.
-
C.
Mokpo
Mokpo is a coastal city in South Jeolla Province, South Korea, known as a regional transportation hub and gateway to numerous nearby islands.
-
D.
Sokcho
Sokcho is a coastal city in northeastern South Korea known for its beaches, seafood, and proximity to Seoraksan National Park.
-
E.
Neryungri
Neryungri is a major coal-mining and industrial city in southeastern Siberia, Russia, known as one of the key urban centers of the Sakha Republic (Yakutia).
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6885a127c8190867b059bdccf13ff |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e1d43e948190843f1cef3ce2004e |
completed | March 27, 2026, 8 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7b8b9a0e881909ee8f92ecb6fef66 |
completed | March 28, 2026, 11:17 a.m. |
Created at: March 27, 2026, 2:34 p.m.