Triple
T16360347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Incheon |
E397293
|
entity |
| Predicate | romanization |
P2508
|
FINISHED |
| Object | Inchŏn |
E27787
|
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: Inchŏn | Statement: [Incheon, romanization, Inchŏn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Inchŏn Context triple: [Incheon, romanization, Inchŏn]
-
A.
Incheon
chosen
Incheon is a major port city in northwestern South Korea, known for its international airport and role as a key transportation and economic hub.
-
B.
Jinju-si
Jinju-si is a city in South Gyeongsang Province, South Korea, known for its historic Jinju Fortress and the annual Namgang Yudeung (Lantern) Festival.
-
C.
Chemulpo (Incheon)
Chemulpo (now part of Incheon, South Korea) was a major late 19th–early 20th century treaty port and strategic harbor on the Yellow Sea, important in international trade and naval operations.
-
D.
Gimcheon
Gimcheon is a city in North Gyeongsang Province, South Korea, known as a regional transportation hub and administrative center.
-
E.
Daegu
Daegu is a major metropolitan city in southeastern South Korea known for its textile industry, electronics manufacturing, and cultural festivals.
- 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2fad241848190a9f32c7b050f20a5 |
completed | April 18, 2026, 3:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004575157c819098dbf27cf6641ff4 |
completed | May 10, 2026, 8:44 a.m. |
Created at: April 10, 2026, 5:08 a.m.