Triple
T1152055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JR Saikyo Line |
E23696
|
entity |
| Predicate | servesArea |
P82
|
FINISHED |
| Object |
Omiya
Omiya is a major commercial and transportation hub in Saitama Prefecture, Japan, known for its busy railway station and urban center.
|
E250535
|
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: Omiya | Statement: [JR Saikyo Line, servesArea, Omiya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Omiya Context triple: [JR Saikyo Line, servesArea, Omiya]
-
A.
Toshima
Toshima is a special ward in northwest Tokyo known for the major commercial and entertainment hub of Ikebukuro and its dense urban residential districts.
-
B.
Musashino
Musashino is a suburban city in western Tokyo, Japan, known for the popular Kichijoji district and its blend of residential neighborhoods, shopping areas, and parks.
-
C.
Maishima
Maishima is a man-made island in Osaka, Japan, known for its sports facilities, event venues, and waterfront recreational areas.
-
D.
Moriguchi
Moriguchi is a city in Japan’s Kansai region that forms part of the Osaka metropolitan area and serves as a residential and commercial hub.
-
E.
Ashiya
Ashiya is an affluent coastal city in Japan’s Hyōgo Prefecture, known for its upscale residential neighborhoods and proximity to both Kobe and Osaka.
- 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: Omiya Triple: [JR Saikyo Line, servesArea, Omiya]
Generated description
Omiya is a major commercial and transportation hub in Saitama Prefecture, Japan, known for its busy railway station and urban center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Omiya Target entity description: Omiya is a major commercial and transportation hub in Saitama Prefecture, Japan, known for its busy railway station and urban center.
-
A.
Toshima
Toshima is a special ward in northwest Tokyo known for the major commercial and entertainment hub of Ikebukuro and its dense urban residential districts.
-
B.
Musashino
Musashino is a suburban city in western Tokyo, Japan, known for the popular Kichijoji district and its blend of residential neighborhoods, shopping areas, and parks.
-
C.
Maishima
Maishima is a man-made island in Osaka, Japan, known for its sports facilities, event venues, and waterfront recreational areas.
-
D.
Moriguchi
Moriguchi is a city in Japan’s Kansai region that forms part of the Osaka metropolitan area and serves as a residential and commercial hub.
-
E.
Ashiya
Ashiya is an affluent coastal city in Japan’s Hyōgo Prefecture, known for its upscale residential neighborhoods and proximity to both Kobe and Osaka.
- 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_69a493f0d32c8190ac74bad3c87f2641 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc8d2dd8819081c779d408c2651d |
completed | March 1, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae7190fb84819095e6ebf2eeb50148 |
completed | March 9, 2026, 7:06 a.m. |
| NEDg | Description generation | batch_69ae75ad4f188190ba6edb78f0c32843 |
completed | March 9, 2026, 7:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae7610cb28819084c1898c4103aceb |
completed | March 9, 2026, 7:26 a.m. |
Created at: March 1, 2026, 7:44 p.m.