Triple
T2991015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jinan |
E80751
|
entity |
| Predicate | hasChineseName |
P4878
|
FINISHED |
| Object | 济南 |
E80751
|
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: 济南 | Statement: [Jinan, hasChineseName, 济南]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 济南 Context triple: [Jinan, hasChineseName, 济南]
-
A.
Jinan
chosen
Jinan is the capital city of Shandong Province in eastern China, known for its numerous natural springs and rich historical and cultural heritage.
-
B.
Weifang
Weifang is a prefecture-level city in eastern China known for its kite-making tradition and annual international kite festival.
-
C.
Zibo
Zibo is an industrial and historical city in eastern China known for its ceramics, petrochemical industry, and role as a former capital of the ancient State of Qi.
-
D.
Linyi
Linyi is a major prefecture-level city in southeastern Shandong Province, China, known for its large population, historical significance, and role as a regional commercial and logistics hub.
-
E.
Rizhao
Rizhao is a coastal city in eastern China known for its sunny climate, beaches, and port on the Yellow Sea.
- 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_69ad8b16c3488190b47b6aa7a59a335b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99de55208190bc56ecbe08638e5a |
completed | March 8, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b109039cfc8190a286c83df752967e |
completed | March 11, 2026, 6:17 a.m. |
Created at: March 8, 2026, 2:59 p.m.