Triple
T14762569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seodaemun-gu |
E346906
|
entity |
| Predicate | romanization |
P2508
|
FINISHED |
| Object |
Sŏdaemun-gu
Sŏdaemun-gu is a central district of Seoul, South Korea, known for its historic sites, universities, and vibrant urban neighborhoods.
|
E1140022
|
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: Sŏdaemun-gu | Statement: [Seodaemun-gu, romanization, Sŏdaemun-gu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sŏdaemun-gu Context triple: [Seodaemun-gu, romanization, Sŏdaemun-gu]
-
A.
Kangseo-gu
Kangseo-gu is the romanized name of Gangseo District, an administrative district of Seoul, South Korea.
-
B.
Yeonsu-gu
Yeonsu-gu is an administrative district of Incheon, South Korea, known for its coastal location, modern residential areas, and proximity to the Songdo International Business District.
-
C.
Seongbuk-gu
Seongbuk-gu is a district in northern Seoul, South Korea, known for its residential neighborhoods, cultural sites, and several major universities.
-
D.
Suyeong-gu
Suyeong-gu is a coastal district in the city of Busan, South Korea, known for its urban neighborhoods and proximity to popular beaches.
-
E.
Gangseo-gu
Gangseo-gu is a western coastal district of Busan, South Korea, known for its industrial complexes, logistics hubs, and proximity to Gimhae International Airport.
- 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: Sŏdaemun-gu Triple: [Seodaemun-gu, romanization, Sŏdaemun-gu]
Generated description
Sŏdaemun-gu is a central district of Seoul, South Korea, known for its historic sites, universities, and vibrant urban neighborhoods.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sŏdaemun-gu Target entity description: Sŏdaemun-gu is a central district of Seoul, South Korea, known for its historic sites, universities, and vibrant urban neighborhoods.
-
A.
Kangseo-gu
Kangseo-gu is the romanized name of Gangseo District, an administrative district of Seoul, South Korea.
-
B.
Yeonsu-gu
Yeonsu-gu is an administrative district of Incheon, South Korea, known for its coastal location, modern residential areas, and proximity to the Songdo International Business District.
-
C.
Seongbuk-gu
Seongbuk-gu is a district in northern Seoul, South Korea, known for its residential neighborhoods, cultural sites, and several major universities.
-
D.
Suyeong-gu
Suyeong-gu is a coastal district in the city of Busan, South Korea, known for its urban neighborhoods and proximity to popular beaches.
-
E.
Gangseo-gu
Gangseo-gu is a western coastal district of Busan, South Korea, known for its industrial complexes, logistics hubs, and proximity to Gimhae International Airport.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7f3a1608190b1b17624003a0c7f |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69febfd1a1b48190b3b69b2841f643a3 |
completed | May 9, 2026, 5:02 a.m. |
| NEDg | Description generation | batch_69fec17d53448190942e5df10ffad4e5 |
completed | May 9, 2026, 5:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fec2300c4481908892a6515d99c12f |
completed | May 9, 2026, 5:12 a.m. |
Created at: April 10, 2026, 1:30 a.m.