Triple
T15474581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hebi |
E376751
|
entity |
| Predicate | hasShortChineseName |
P54502
|
FINISHED |
| Object | 鹤壁 |
E1159270
|
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: 鹤壁 | Statement: [Hebi, hasShortChineseName, 鹤壁]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 鹤壁 Context triple: [Hebi, hasShortChineseName, 鹤壁]
-
A.
鹤壁市
chosen
鹤壁市 is a prefecture-level city in northern Henan Province, China, known for its coal resources and developing industrial economy.
-
B.
平顶山
平顶山是位于中国河南省中部、以煤炭资源和重工业著称的地级市。
-
C.
邯郸市
邯郸市 is a historically significant prefecture-level city in southern Hebei Province, China, known as an ancient capital and important industrial and transportation hub in the North China Plain.
-
D.
漯河市
漯河市 is a prefecture-level city in central China’s Henan Province, known as an important transportation hub and food-processing center along the middle reaches of the Yellow River region.
-
E.
Hengshui
Hengshui is a prefecture-level city in southeastern Hebei Province, China, known for its traditional culture, agriculture, and growing industrial base.
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f6e859481909c3d08343b7ad27c |
completed | April 16, 2026, 1:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff36595bfc8190a0d60b3cb875ccc5 |
completed | May 9, 2026, 1:27 p.m. |
Created at: April 10, 2026, 3:34 a.m.