Triple
T19461362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beihuan Boulevard |
E486878
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Shenzhen road network |
—
|
NE NERFINISHED |
How this triple was built (3 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: Shenzhen road network | Statement: [Beihuan Boulevard, partOf, Shenzhen road network]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shenzhen road network Context triple: [Beihuan Boulevard, partOf, Shenzhen road network]
-
A.
Hong Kong road network
The Hong Kong road network is a dense, highly developed system of highways, tunnels, bridges, and urban streets that supports the territory’s intensive traffic and connects its major districts and outlying areas.
-
B.
Zhuhai urban transport network
The Zhuhai urban transport network is the integrated system of local buses, rail links, and other public transit services that facilitates movement within Zhuhai and connects it to surrounding cities in the Pearl River Delta.
-
C.
Beijing urban road network
The Beijing urban road network is an extensive, hierarchical system of ring roads, arterial avenues, and expressways that organizes and connects the Chinese capital’s dense urban fabric and surrounding metropolitan area.
-
D.
Taipei road network
The Taipei road network is an extensive urban transportation system of highways, arterial roads, bridges, and streets that supports the dense traffic and connectivity needs of Taiwan’s capital city.
-
E.
expressways of Shenzhen
The expressways of Shenzhen form a dense, modern highway network that connects its urban districts and surrounding regions, supporting the city’s rapid economic growth and high-volume traffic.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shenzhen road network Target entity description: The Shenzhen road network is an extensive, high-capacity urban roadway system that connects and supports the fast-growing metropolis of Shenzhen, China.
-
A.
Hong Kong road network
The Hong Kong road network is a dense, highly developed system of highways, tunnels, bridges, and urban streets that supports the territory’s intensive traffic and connects its major districts and outlying areas.
-
B.
Zhuhai urban transport network
The Zhuhai urban transport network is the integrated system of local buses, rail links, and other public transit services that facilitates movement within Zhuhai and connects it to surrounding cities in the Pearl River Delta.
-
C.
Beijing urban road network
The Beijing urban road network is an extensive, hierarchical system of ring roads, arterial avenues, and expressways that organizes and connects the Chinese capital’s dense urban fabric and surrounding metropolitan area.
-
D.
Taipei road network
The Taipei road network is an extensive urban transportation system of highways, arterial roads, bridges, and streets that supports the dense traffic and connectivity needs of Taiwan’s capital city.
-
E.
expressways of Shenzhen
chosen
The expressways of Shenzhen form a dense, modern highway network that connects its urban districts and surrounding regions, supporting the city’s rapid economic growth and high-volume traffic.
- F. None of above.
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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633c983f481908b2684dc4380b889 |
completed | April 20, 2026, 2:10 p.m. |
Created at: April 10, 2026, 1:38 p.m.