Triple
T16928391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yongin |
E410636
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Suji-gu
Suji-gu is an urban district in the city of Yongin, South Korea, known for its residential developments, educational institutions, and proximity to Seoul.
|
E1373753
|
NE FINISHED |
How this triple was built (4 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: Suji-gu | Statement: [Yongin, hasDistrict, Suji-gu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suji-gu Context triple: [Yongin, hasDistrict, Suji-gu]
-
A.
Izumi-ku
Izumi-ku is a northern residential and commercial ward of Sendai in Miyagi Prefecture, Japan, known for its suburban neighborhoods and shopping centers.
-
B.
Suminoe Ward
Suminoe Ward is one of Osaka City's 24 wards, known for its coastal location, residential districts, and industrial and port-related facilities.
-
C.
Hamamatsuchō
Hamamatsuchō is a business and transportation district in Tokyo known for its major train and monorail stations, office towers, and proximity to Tokyo Bay.
-
D.
Suginami
Suginami is a residential ward in western Tokyo, Japan, known for its quiet neighborhoods, anime studios, and vibrant local shopping streets.
-
E.
Sawara-ku
Sawara-ku is one of the wards of Fukuoka City in Japan, known for its mix of residential areas, universities, and coastal attractions along the Sea of Japan.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Suji-gu Triple: [Yongin, hasDistrict, Suji-gu]
Generated description
Suji-gu is an urban district in the city of Yongin, South Korea, known for its residential developments, educational institutions, and proximity to Seoul.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Suji-gu Target entity description: Suji-gu is an urban district in the city of Yongin, South Korea, known for its residential developments, educational institutions, and proximity to Seoul.
-
A.
Izumi-ku
Izumi-ku is a northern residential and commercial ward of Sendai in Miyagi Prefecture, Japan, known for its suburban neighborhoods and shopping centers.
-
B.
Suminoe Ward
Suminoe Ward is one of Osaka City's 24 wards, known for its coastal location, residential districts, and industrial and port-related facilities.
-
C.
Hamamatsuchō
Hamamatsuchō is a business and transportation district in Tokyo known for its major train and monorail stations, office towers, and proximity to Tokyo Bay.
-
D.
Suginami
Suginami is a residential ward in western Tokyo, Japan, known for its quiet neighborhoods, anime studios, and vibrant local shopping streets.
-
E.
Sawara-ku
Sawara-ku is one of the wards of Fukuoka City in Japan, known for its mix of residential areas, universities, and coastal attractions along the Sea of Japan.
- F. None of above. chosen
Provenance (5 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_69d886c7b1e481908c3766dfa8c13458 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cdf3fc3c8190a884f7ecd5c47adb |
completed | April 18, 2026, 6:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a072b64b16c8190ab23bfc8a2ec7b66 |
completed | May 15, 2026, 2:19 p.m. |
| NEDg | Description generation | batch_6a072d79ae348190a078fb5441c6466b |
completed | May 15, 2026, 2:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a072e930e948190ac19fa2b81639922 |
completed | May 15, 2026, 2:32 p.m. |
Created at: April 10, 2026, 5:30 a.m.