Triple
T5033673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blagoveshchensk |
E113367
|
entity |
| Predicate | hasSisterCity |
P919
|
FINISHED |
| Object | Hohhot |
E80543
|
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: Hohhot | Statement: [Blagoveshchensk, hasSisterCity, Hohhot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hohhot Context triple: [Blagoveshchensk, hasSisterCity, Hohhot]
-
A.
Hohhot
chosen
Hohhot is the capital and largest city of Inner Mongolia in northern China, known as a regional center of politics, culture, and industry.
-
B.
Chifeng
Chifeng is a prefecture-level city in southeastern Inner Mongolia, China, known for its mix of grassland, forest, and historical sites linked to ancient nomadic cultures.
-
C.
Wuhai
Wuhai is a prefecture-level industrial city in western Inner Mongolia, China, known for its coal mining, chemical industries, and location along the Yellow River.
-
D.
Hulunbuir
Hulunbuir is a vast prefecture-level city in northeastern China renowned for its expansive grasslands, diverse ethnic cultures, and rich natural resources.
-
E.
Qiqihar
Qiqihar is a major industrial city in northeastern China’s Heilongjiang province, known historically as a regional transportation hub and center for heavy industry.
- 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_69bd443775e48190a646ffbfc4334723 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd73b68d8c8190b8e04fb406abdb0f |
completed | March 20, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bea477efec8190a84a0186f5517a43 |
completed | March 21, 2026, 2 p.m. |
Created at: March 20, 2026, 1:36 p.m.