Triple
T6248058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seocho District |
E139771
|
entity |
| Predicate | hasMcCuneReischauerRomanization |
P23170
|
FINISHED |
| Object |
Sŏch'o-gu
Sŏch'o-gu is the McCune–Reischauer romanization of Seocho District, a major administrative and residential area in southern Seoul, South Korea.
|
E607544
|
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: Sŏch'o-gu | Statement: [Seocho District, hasMcCuneReischauerRomanization, Sŏch'o-gu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sŏch'o-gu Context triple: [Seocho District, hasMcCuneReischauerRomanization, Sŏch'o-gu]
-
A.
Kangseo-gu
Kangseo-gu is the romanized name of Gangseo District, an administrative district of Seoul, South Korea.
-
B.
Pusanjin-gu
Pusanjin-gu is a central urban district of Busan, South Korea, known for its major commercial areas, transportation hubs, and dense residential neighborhoods.
-
C.
Kŭmchŏng-gu
Kŭmchŏng-gu is the McCune–Reischauer romanization of Geumjeong District, an administrative district in Busan, South Korea.
-
D.
Suyŏng-gu
Suyŏng-gu is an urban district of Busan, South Korea, known for its coastal location and role as a residential and commercial hub within the city.
-
E.
Seo-gu
Seo-gu is a district of the metropolitan city of Daejeon in South Korea, known for its residential areas, commercial centers, and educational institutions.
- 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: Sŏch'o-gu Triple: [Seocho District, hasMcCuneReischauerRomanization, Sŏch'o-gu]
Generated description
Sŏch'o-gu is the McCune–Reischauer romanization of Seocho District, a major administrative and residential area in southern Seoul, South Korea.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sŏch'o-gu Target entity description: Sŏch'o-gu is the McCune–Reischauer romanization of Seocho District, a major administrative and residential area in southern Seoul, South Korea.
-
A.
Kangseo-gu
Kangseo-gu is the romanized name of Gangseo District, an administrative district of Seoul, South Korea.
-
B.
Pusanjin-gu
Pusanjin-gu is a central urban district of Busan, South Korea, known for its major commercial areas, transportation hubs, and dense residential neighborhoods.
-
C.
Kŭmchŏng-gu
Kŭmchŏng-gu is the McCune–Reischauer romanization of Geumjeong District, an administrative district in Busan, South Korea.
-
D.
Suyŏng-gu
Suyŏng-gu is an urban district of Busan, South Korea, known for its coastal location and role as a residential and commercial hub within the city.
-
E.
Seo-gu
Seo-gu is a district of the metropolitan city of Daejeon in South Korea, known for its residential areas, commercial centers, and educational institutions.
- 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_69c008b1c5088190ae6de2555fc05ad8 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0633a9a048190856d5247d3b28a2e |
completed | March 22, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e406787881908648872228d6eac9 |
completed | March 27, 2026, 8:09 p.m. |
| NEDg | Description generation | batch_69c6e61218c4819084c170611077f0e6 |
completed | March 27, 2026, 8:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6e7cc21548190b302e2e31f9cadd0 |
completed | March 27, 2026, 8:25 p.m. |
Created at: March 22, 2026, 4:23 p.m.