Triple
T23216945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 神戸市 |
E580770
|
entity |
| Predicate | sisterCity |
P1072
|
FINISHED |
| Object | 天津 |
—
|
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: 天津 | Statement: [神戸市, sisterCity, 天津]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 天津 Context triple: [神戸市, sisterCity, 天津]
-
A.
Tianjin
chosen
Tianjin is a major port city and industrial hub in northern China, located near Beijing along the Bohai Sea.
-
B.
青島
青島 is a small Japanese island best known for its large population of semi-feral cats that attract many tourists.
-
C.
Tangshan Prefecture-level City
Tangshan Prefecture-level City is an important industrial and port city in northeastern Hebei Province, China, known for its heavy industry, coal mining, and proximity to the Bohai Sea.
-
D.
Pinghu City
Pinghu City is a county-level coastal city in northern Zhejiang Province, China, known for its manufacturing industry and proximity to Shanghai across Hangzhou Bay.
-
E.
Tân An
Tân An is a city in southern Vietnam that serves as an administrative, economic, and cultural hub in the Mekong Delta region.
- 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_69e2460389408190be74f41d217799a9 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f19165949c81908e4d66a8a2b0a25a |
completed | April 29, 2026, 5:04 a.m. |
Created at: April 17, 2026, 4:08 p.m.