Triple
T18311853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wuzhou |
E438644
|
entity |
| Predicate | hasCountyLevelCity |
P27799
|
FINISHED |
| Object | Cenxi |
—
|
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: Cenxi | Statement: [Wuzhou, hasCountyLevelCity, Cenxi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cenxi Context triple: [Wuzhou, hasCountyLevelCity, Cenxi]
-
A.
Cenxi
chosen
Cenxi is a county-level city administered by Wuzhou in the Guangxi Zhuang Autonomous Region of southern China.
-
B.
Tianeti
Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
-
C.
Cenon
Cenon is a suburban commune in southwestern France located just east of the city of Bordeaux.
-
D.
Sicong
Sicong is a given name most notably associated with Ma Sicong, a prominent 20th-century Chinese composer and violinist.
-
E.
Kunka
Kunka is the original name of the Historic Walled Town of Cuenca, a UNESCO-listed medieval city in central Spain renowned for its dramatic clifftop setting and well-preserved architecture.
- 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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50219cd548190b8da5f402d5da773 |
completed | April 19, 2026, 4:26 p.m. |
Created at: April 10, 2026, 10:36 a.m.