Triple
T13964083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linfen |
E335875
|
entity |
| Predicate | borderingPrefectureLevelCity |
P49472
|
FINISHED |
| Object | Yuncheng |
E336862
|
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: Yuncheng | Statement: [Linfen, borderingPrefectureLevelCity, Yuncheng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yuncheng Context triple: [Linfen, borderingPrefectureLevelCity, Yuncheng]
-
A.
Yuncheng
chosen
Yuncheng is a major city in southern Shanxi Province, China, known for its historical sites and role as a regional transportation and economic hub.
-
B.
Licheng
Licheng is the courtesy name of the Daoguang Emperor, a Qing dynasty ruler of China in the early 19th century.
-
C.
Yongcheng
Yongcheng was a Qing dynasty imperial prince, known as one of the sons of the Qianlong Emperor of China.
-
D.
Jianye
Jianye is an ancient name for the city now known as Nanjing, a historically significant capital in several Chinese dynasties.
-
E.
Changshou
Changshou was a Chinese imperial era name used during the reign of Empress Wu Zetian in the Tang dynasty.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e7e24f08190ba939a8044860033 |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc321c600819085052392de9b0b53 |
completed | May 6, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:18 p.m.