Triple
T17794201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tong'an District |
E444246
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Haicang 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: Haicang District | Statement: [Tong'an District, borderedBy, Haicang District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haicang District Context triple: [Tong'an District, borderedBy, Haicang District]
-
A.
Haicang District
chosen
Haicang District is an urban district of Xiamen in Fujian Province, China, known for its industrial development and port facilities across the strait from Taiwan.
-
B.
Dapeng New District
Dapeng New District is a coastal administrative area of Shenzhen known for its scenic beaches, ecological reserves, and historic Dapeng Fortress.
-
C.
Qiaokou District
Qiaokou District is an urban district of Wuhan in Hubei Province, China, known for its dense residential areas and commercial activity.
-
D.
Nanshan District
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.
-
E.
Haizhou District
Haizhou District is an urban administrative district and central area of Lianyungang City in Jiangsu Province, China.
- 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_69d8b9efe370819095cd219b143ae727 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e487993a6c8190805e06d93dfc0dce |
completed | April 19, 2026, 7:43 a.m. |
Created at: April 10, 2026, 10:13 a.m.