Triple
T15861583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jiangyin |
E384599
|
entity |
| Predicate | connectedTo |
P37
|
FINISHED |
| Object | Jingjiang |
E1138205
|
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: Jingjiang | Statement: [Jiangyin, connectedTo, Jingjiang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jingjiang Context triple: [Jiangyin, connectedTo, Jingjiang]
-
A.
Jingjiang
chosen
Jingjiang is a county-level city in Jiangsu Province, China, situated along the Yangtze River and known for its river port and industrial economy.
-
B.
Jiangde
Jiangde is a riverside city in China situated along the Xin’an River, known for its scenic landscapes and water-centered local life.
-
C.
Zhenjiang
Zhenjiang is a historic port city in eastern China known for its strategic location on the Yangtze River and its rich cultural and culinary heritage.
-
D.
Qianjiang
Qianjiang is a city in China known for its regional industry and cultural exchanges, including international town twinning partnerships.
-
E.
Liyang
Liyang is a county-level city in Jiangsu Province, China, known for its scenic attractions such as Tianmu Lake and its administration under the prefecture-level city of Changzhou.
- 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_69d86da422088190aac39e32e6c68429 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1555b952481909246f5ebf53df2a9 |
completed | April 16, 2026, 9:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe69332c81909aa57e64de163cbe |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 4:50 a.m.