Triple
T4419942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jialing River |
E95071
|
entity |
| Predicate | cityOnRiver |
P165
|
FINISHED |
| Object | Nanchong |
E276212
|
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: Nanchong | Statement: [Jialing River, cityOnRiver, Nanchong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nanchong Context triple: [Jialing River, cityOnRiver, Nanchong]
-
A.
Nanchong
chosen
Nanchong is a major city in northeastern Sichuan Province, China, known as a regional transportation and economic hub with a long historical and cultural heritage.
-
B.
Deyang
Deyang is an industrial city in southwestern China known for its heavy machinery manufacturing and location near Chengdu in Sichuan Province.
-
C.
Mianyang
Mianyang is a major city in southwestern China known as an important industrial and technological center within Sichuan Province.
-
D.
Langzhong
Langzhong is an ancient county-level city in Sichuan, China, renowned for its well-preserved historic old town and traditional architecture along the Jialing River.
-
E.
Yibin
Yibin is a historic prefecture-level city in southwestern China known as the "First City on the Yangtze River," where the Jinsha and Min rivers converge to form the Yangtze.
- 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_69b3453a36908190b95a79a297ca083c |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3551fae7c8190abafda0d78f02d89 |
completed | March 13, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6374ffbd081908c96847ec2d25cee |
completed | March 15, 2026, 4:36 a.m. |
Created at: March 12, 2026, 11:29 p.m.