Triple
T19580722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northeast China rail network |
E489979
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Hunchun |
—
|
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: Hunchun | Statement: [Northeast China rail network, connects, Hunchun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hunchun Context triple: [Northeast China rail network, connects, Hunchun]
-
A.
Hunchun
chosen
Hunchun is a border city in northeastern China’s Jilin Province, known for its strategic location near the junction of China, Russia, and North Korea and its role in regional trade and development.
-
B.
Baishan
Baishan is a prefecture-level city in southeastern Jilin Province, China, known for its mountainous terrain, forest resources, and proximity to Changbai Mountain.
-
C.
Yanji
Yanji is a city in northeastern China’s Jilin Province, known as a cultural and economic center of the ethnic Korean community near the North Korean border.
-
D.
Hegang
Hegang is a coal-mining city in northeastern Heilongjiang Province, China, located near the Russian border along the Amur River region.
-
E.
Shuangyashan
Shuangyashan is a coal-mining and industrial city in northeastern China known for its energy resources and heavy industry.
- 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e640281b7c8190be44268a58df058f |
completed | April 20, 2026, 3:03 p.m. |
Created at: April 10, 2026, 1:42 p.m.