Triple
T294125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Asia |
E6055
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Kathmandu |
E32411
|
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: Kathmandu | Statement: [South Asia, hasMajorCity, Kathmandu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kathmandu Context triple: [South Asia, hasMajorCity, Kathmandu]
-
A.
Kathmandu
chosen
Kathmandu is the capital and largest city of Nepal, serving as the country’s political, cultural, and economic center.
-
B.
Nepal
Nepal is a landlocked South Asian country in the Himalayas, known for Mount Everest, its rich cultural heritage, and its location between India and China.
-
C.
Guwahati
Guwahati is a major city in northeastern India, serving as a key cultural, economic, and transportation hub for the region.
-
D.
Ulaanbaatar
Ulaanbaatar is the capital and largest city of Mongolia, serving as its political, economic, and cultural center.
-
E.
Chandigarh
Chandigarh is a planned city in northern India, renowned for its modernist architecture and urban design largely conceived by the Swiss-French architect Le Corbusier.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2e978420881908488df342a7d5e90 |
completed | Feb. 28, 2026, 1:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3a5d514388190ac0f748a406ae43e |
completed | March 1, 2026, 2:35 a.m. |
Created at: Feb. 28, 2026, 1:06 p.m.