Triple
T10109982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 湘语 |
E218213
|
entity |
| Predicate | majorCityWhereSpoken |
P35609
|
FINISHED |
| Object | 株洲市 |
E165476
|
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: 株洲市 | Statement: [湘语, majorCityWhereSpoken, 株洲市]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 株洲市 Context triple: [湘语, majorCityWhereSpoken, 株洲市]
-
A.
浏阳
浏阳是中国湖南省东部的一座县级市，以烟花爆竹产业和红色革命历史而闻名。
-
B.
Loudi
Loudi is a prefecture-level city in south-central China known for its role as an industrial and transportation hub within Hunan Province.
-
C.
Zhuzhou
chosen
Zhuzhou is a major industrial and transportation hub city in south-central China, known especially for its rail transit and manufacturing industries.
-
D.
Changde
Changde is a city in northwestern Hunan Province, China, historically significant as a major battleground during the Second Sino-Japanese War.
-
E.
Xiangtan
Xiangtan is a prefecture-level city in central Hunan Province, China, known as an important industrial and commercial hub and for encompassing Shaoshan, the birthplace of Mao Zedong.
- 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_69ca83da93fc8190b54e44bc2b34857c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd0cdb3c88190a74f75bf865664f3 |
completed | April 2, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2cc1805d08190bc39aadf1e84a569 |
completed | April 5, 2026, 8:54 p.m. |
Created at: March 30, 2026, 9:03 p.m.