Triple
T3637503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Taipei City |
E77106
|
entity |
| Predicate | hasSisterCity |
P919
|
FINISHED |
| Object | Goyang |
E232375
|
NE FINISHED |
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: Goyang | Statement: [New Taipei City, hasSisterCity, Goyang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Goyang Context triple: [New Taipei City, hasSisterCity, Goyang]
-
A.
Goyang
chosen
Goyang is a major satellite city northwest of Seoul in South Korea, known for its rapid urban development, residential districts, and cultural attractions such as Ilsan Lake Park and KINTEX.
-
B.
Yangju
Yangju is a city in northwestern South Korea known for its mix of suburban residential areas, light industry, and proximity to Seoul.
-
C.
Miryang
Miryang is a city in South Gyeongsang Province, South Korea, known for its scenic river valley setting, historical sites, and role as a regional transport and educational hub.
-
D.
Gapcheon
Gapcheon is a major river flowing through the city of Daejeon in South Korea, serving as a central natural and recreational landmark.
-
E.
Gaya-dong
Gaya-dong is a neighborhood in Busan, South Korea, known as a residential and commercial area within the central urban zone of the city.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ad85dd0be48190b738990cb20c4731 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc328e5e481909d26318c743bc84a |
completed | March 8, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b44f23298481909d313d6b3f8013cd |
completed | March 13, 2026, 5:53 p.m. |
Created at: March 8, 2026, 3:24 p.m.