Triple
T17508925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jinmen County |
E426397
|
entity |
| Predicate | hasMajorIsland |
P756
|
FINISHED |
| Object | Lieyu |
—
|
NE NERFINISHED |
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: Lieyu | Statement: [Jinmen County, hasMajorIsland, Lieyu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lieyu Context triple: [Jinmen County, hasMajorIsland, Lieyu]
-
A.
Lieyu
chosen
Lieyu is a small island township of Kinmen County, administered by Taiwan and located just off the coast of mainland China.
-
B.
Kaiya
Kaiya is a feminine given name used in various cultures, often associated with meanings related to the sea, forgiveness, or purity.
-
C.
Lyolik
Lyolik is a comedic criminal character from the classic Soviet film "The Diamond Arm," known for his bumbling attempts at carrying out a smuggling scheme.
-
D.
Jinyu
Jinyu is a major variety of the Jin group of Chinese dialects spoken primarily in northern China, especially in Shanxi and surrounding regions.
-
E.
Shiqi
Shiqi was a historical administrative and commercial center that served as the capital of Xiangshan County in Guangdong during the Qing Empire.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4525a43208190b8728214767428c0 |
completed | April 19, 2026, 3:56 a.m. |
Created at: April 10, 2026, 5:48 a.m.