Triple
T17729990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asia area |
E442560
|
entity |
| Predicate | locatedInDistrict |
P40
|
FINISHED |
| Object | Nanshan District |
—
|
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: Nanshan District | Statement: [Asia area, locatedInDistrict, Nanshan District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nanshan District Context triple: [Asia area, locatedInDistrict, Nanshan District]
-
A.
Nanshan District
chosen
Nanshan District is a major urban district of Shenzhen, China, known as a key technology and innovation hub that hosts many leading tech companies and research institutions.
-
B.
Yuanbao District
Yuanbao District is an urban administrative district within the city of Dandong in Liaoning Province, northeastern China.
-
C.
Tianxin District
Tianxin District is a central urban district of Changsha, the capital city of Hunan Province in China, known for its historical sites and commercial areas.
-
D.
Pengjiang District
Pengjiang District is the central urban district and administrative, economic, and cultural core of Jiangmen City in Guangdong Province, China.
-
E.
Shuangxi District
Shuangxi District is a rural, mountainous district in eastern New Taipei City, Taiwan, known for its rivers, old streets, and natural scenery.
- 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e478e5ba7c81908f8b06eb6859067f |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 10:08 a.m.