Triple
T10002072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luoyang |
E197350
|
entity |
| Predicate | chineseName |
P4878
|
FINISHED |
| Object | 洛阳 |
E197350
|
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: 洛阳 | Statement: [Luoyang, chineseName, 洛阳]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 洛阳 Context triple: [Luoyang, chineseName, 洛阳]
-
A.
南阳
南阳 is a prefecture-level city in southwestern Henan Province, China, known as a historic cultural center and important transportation hub in the region.
-
B.
Luoyang
chosen
Luoyang is one of China’s oldest and most historically significant cities, renowned as an ancient imperial capital and cultural center along the Yellow River.
-
C.
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。
-
D.
Dengfeng
Dengfeng is a historic city in Henan Province, China, renowned for its ancient religious and cultural sites, including temples and observatories associated with Chinese cosmology and martial arts traditions.
-
E.
Xuchang
Xuchang is a historically significant city in central China, known as a former capital during the Three Kingdoms period and now an important industrial and transportation hub.
- 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_69ca82f3b61c81908ecc2c1c96dbc2e4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdcc9078788190a4e75dd7ff830c63 |
completed | April 2, 2026, 1:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d25854c524819081315b1a8faf335e |
completed | April 5, 2026, 12:40 p.m. |
Created at: March 30, 2026, 8:51 p.m.