Triple
T10028794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gyeongbu Line |
E204798
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Gumi |
E531414
|
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: Gumi | Statement: [Gyeongbu Line, passesThrough, Gumi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gumi Context triple: [Gyeongbu Line, passesThrough, Gumi]
-
A.
Gumi
chosen
Gumi is an industrial city in South Korea’s North Gyeongsang Province, known as a major electronics manufacturing hub.
-
B.
Emori
Emori is a Japanese given name that can be used for individuals of any gender.
-
C.
Oimachi
Oimachi is a commercial and residential district in Tokyo known for its busy train hub, shopping streets, and convenient access to central Shinagawa and other parts of the city.
-
D.
Mitaka
Mitaka is a city in western Tokyo, Japan, known for its residential neighborhoods, parks, and the Ghibli Museum.
-
E.
Sugamo
Sugamo is a Tokyo neighborhood popularly known as the “Harajuku for old ladies,” famed for its Jizō-dōri shopping street and large elderly clientele.
- 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_69ca834d77188190ad645e33e8ca3200 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcde51c408190afb34010b1707014 |
completed | April 2, 2026, 2:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d282351ebc8190b22bf3964823b0ee |
completed | April 5, 2026, 3:39 p.m. |
Created at: March 30, 2026, 8:54 p.m.