Triple
T18311852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wuzhou |
E438644
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Cenxi
Cenxi is a county-level city administered by Wuzhou in the Guangxi Zhuang Autonomous Region of southern China.
|
E1316397
|
NE FINISHED |
How this triple was built (4 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, hasSubdivision, Cenxi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cenxi Context triple: [Wuzhou, hasSubdivision, Cenxi]
-
A.
Tianeti
Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
-
B.
Cenon
Cenon is a suburban commune in southwestern France located just east of the city of Bordeaux.
-
C.
Sicong
Sicong is a given name most notably associated with Ma Sicong, a prominent 20th-century Chinese composer and violinist.
-
D.
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.
-
E.
Tunxi
Tunxi is an urban district of Huangshan City in Anhui Province, China, known as its central administrative and commercial hub and a gateway to the nearby Huangshan (Yellow Mountain) scenic area.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Cenxi Triple: [Wuzhou, hasSubdivision, Cenxi]
Generated description
Cenxi is a county-level city administered by Wuzhou in the Guangxi Zhuang Autonomous Region of southern China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cenxi Target entity description: Cenxi is a county-level city administered by Wuzhou in the Guangxi Zhuang Autonomous Region of southern China.
-
A.
Tianeti
Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
-
B.
Cenon
Cenon is a suburban commune in southwestern France located just east of the city of Bordeaux.
-
C.
Sicong
Sicong is a given name most notably associated with Ma Sicong, a prominent 20th-century Chinese composer and violinist.
-
D.
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.
-
E.
Tunxi
Tunxi is an urban district of Huangshan City in Anhui Province, China, known as its central administrative and commercial hub and a gateway to the nearby Huangshan (Yellow Mountain) scenic area.
- F. None of above. chosen
Provenance (5 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. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03bb67638081908ccfc60c03eff94b |
completed | May 12, 2026, 11:44 p.m. |
| NEDg | Description generation | batch_6a03bbda80748190b8e56fb77140ecb9 |
completed | May 12, 2026, 11:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03bc589a548190b6226a104adea97e |
completed | May 12, 2026, 11:48 p.m. |
Created at: April 10, 2026, 10:36 a.m.