Triple
T7782675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baoji |
E221560
|
entity |
| Predicate | chineseName |
P4878
|
FINISHED |
| Object | 宝鸡 |
E221560
|
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: 宝鸡 | Statement: [Baoji, chineseName, 宝鸡]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 宝鸡 Context triple: [Baoji, chineseName, 宝鸡]
-
A.
鳳翔
鳳翔 was the Imperial Japanese Navy’s Hōshō, the world’s first purpose-built aircraft carrier to enter service.
-
B.
Baoji
chosen
Baoji is a major industrial and transportation hub city in western Shaanxi Province, China, known for its manufacturing base and historical sites.
-
C.
Hanzhong
Hanzhong is a historic prefecture-level city in southwestern Shaanxi, China, known as a key gateway between northern and southern China and for its rich cultural and natural landscapes.
-
D.
Tongchuan
Tongchuan is a prefecture-level city in central Shaanxi Province, China, historically known for its coal mining industry and location on the Loess Plateau.
-
E.
Shangluo
Shangluo is a prefecture-level city in southeastern Shaanxi, China, known for its mountainous terrain, rich natural resources, and historical sites.
- 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_69ca83ebbef881909ac47f789145fef7 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cadf1f9c648190ac2b06d0d54035ea |
completed | March 30, 2026, 8:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69caf5e400d881909d6cdeb7eaac3a59 |
completed | March 30, 2026, 10:15 p.m. |
Created at: March 30, 2026, 4:22 p.m.