Triple
T8177103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korail |
E190963
|
entity |
| Predicate | operatesService |
P5884
|
FINISHED |
| Object |
Nuriro
Nuriro is a class of South Korean intercity passenger trains operated by Korail, providing medium-speed rail services on various routes.
|
E763839
|
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: Nuriro | Statement: [Korail, operatesService, Nuriro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nuriro Context triple: [Korail, operatesService, Nuriro]
-
A.
Shimotsuki
Shimotsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk in late 1944.
-
B.
Machimura
Machimura is a Japanese surname most notably associated with Nobutaka Machimura, a prominent Liberal Democratic Party politician and former foreign minister of Japan.
-
C.
Togoshi
Togoshi is a residential and commercial neighborhood in Tokyo’s Shinagawa ward, known for its traditional shopping streets and local atmosphere.
-
D.
Koromo
Koromo was the former name of what is now Toyota City in Aichi Prefecture, Japan, historically known as a regional center before becoming synonymous with the Toyota automobile company.
-
E.
Takamikura
Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
- 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: Nuriro Triple: [Korail, operatesService, Nuriro]
Generated description
Nuriro is a class of South Korean intercity passenger trains operated by Korail, providing medium-speed rail services on various routes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nuriro Target entity description: Nuriro is a class of South Korean intercity passenger trains operated by Korail, providing medium-speed rail services on various routes.
-
A.
Shimotsuki
Shimotsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk in late 1944.
-
B.
Machimura
Machimura is a Japanese surname most notably associated with Nobutaka Machimura, a prominent Liberal Democratic Party politician and former foreign minister of Japan.
-
C.
Togoshi
Togoshi is a residential and commercial neighborhood in Tokyo’s Shinagawa ward, known for its traditional shopping streets and local atmosphere.
-
D.
Koromo
Koromo was the former name of what is now Toyota City in Aichi Prefecture, Japan, historically known as a regional center before becoming synonymous with the Toyota automobile company.
-
E.
Takamikura
Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
- 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_69ca82c1c0a08190bf8692b4d91a03ca |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4aba0dd88190828080d0d89612eb |
completed | March 31, 2026, 4:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfab01c58c81909148dacad2dc7667 |
completed | April 3, 2026, 11:56 a.m. |
| NEDg | Description generation | batch_69cfac76d0f8819090c2bff520db52f4 |
completed | April 3, 2026, 12:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfad04e514819084bf30b8f026c031 |
completed | April 3, 2026, 12:05 p.m. |
Created at: March 30, 2026, 5:40 p.m.