Triple
T9622412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goyang |
E232375
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Yangju |
E235115
|
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: Yangju | Statement: [Goyang, borderedBy, Yangju]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yangju Context triple: [Goyang, borderedBy, Yangju]
-
A.
Yangju
chosen
Yangju is a city in northwestern South Korea known for its mix of suburban residential areas, light industry, and proximity to Seoul.
-
B.
Myeong-bok
Myeong-bok is the given name of Gojong, the 26th king of the Joseon dynasty and first emperor of the Korean Empire.
-
C.
Yangsan-dong
Yangsan-dong is a neighborhood (dong) within the city of Osan in Gyeonggi Province, South Korea.
-
D.
Maengdong-myeon
Maengdong-myeon is a rural township-level administrative area located within Eumseong County in North Chungcheong Province, South Korea.
-
E.
Mungyeong
Mungyeong is a city in South Korea known for its historic mountain passes, scenic hiking trails, and traditional cultural heritage.
- 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_69ca848793ec8190a93a12383a754dc0 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9ad505588190b8c81ce09f1904ec |
completed | April 1, 2026, 10:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d18225f9508190bde23b9d2a40bccc |
completed | April 4, 2026, 9:27 p.m. |
Created at: March 30, 2026, 8:10 p.m.