Triple
T5553187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 湘南新宿ライン |
E145575
|
entity |
| Predicate | 略称 |
P43
|
FINISHED |
| Object |
SSライン
SSラインは、首都圏を南北に結ぶJR東日本の湘南新宿ラインを指す略称である。
|
E536022
|
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: SSライン | Statement: [湘南新宿ライン, 略称, SSライン]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SSライン Context triple: [湘南新宿ライン, 略称, SSライン]
-
A.
SS3
SS3 is an Italian state highway that forms part of the historic Via Flaminia route connecting Rome with central and northeastern Italy.
-
B.
S Line
The S Line is a modern streetcar route in the Salt Lake City area that provides local transit service and links neighborhoods to the broader TRAX light rail network.
-
C.
S Line
The S Line is a route within the Sounder commuter rail system that provides passenger rail service in the Seattle metropolitan area.
-
D.
U Line
U Line is a light metro line in the Seoul metropolitan area that serves the city of Uijeongbu with driverless trains on an elevated and mostly automated system.
-
E.
Kada Line
The Kada Line is a regional railway line in Wakayama Prefecture, Japan, providing local passenger service between Wakayamashi and Kada along the coast.
- 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: SSライン Triple: [湘南新宿ライン, 略称, SSライン]
Generated description
SSラインは、首都圏を南北に結ぶJR東日本の湘南新宿ラインを指す略称である。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SSライン Target entity description: SSラインは、首都圏を南北に結ぶJR東日本の湘南新宿ラインを指す略称である。
-
A.
SS3
SS3 is an Italian state highway that forms part of the historic Via Flaminia route connecting Rome with central and northeastern Italy.
-
B.
S Line
The S Line is a modern streetcar route in the Salt Lake City area that provides local transit service and links neighborhoods to the broader TRAX light rail network.
-
C.
S Line
The S Line is a route within the Sounder commuter rail system that provides passenger rail service in the Seattle metropolitan area.
-
D.
U Line
U Line is a light metro line in the Seoul metropolitan area that serves the city of Uijeongbu with driverless trains on an elevated and mostly automated system.
-
E.
Kada Line
The Kada Line is a regional railway line in Wakayama Prefecture, Japan, providing local passenger service between Wakayamashi and Kada along the coast.
- 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_69c008fb879c81909f5bfa56fadc1d46 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01ff9c9c48190b5e587d58c6515d8 |
completed | March 22, 2026, 4:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04cfc6f808190a39c607f61dcfa32 |
completed | March 22, 2026, 8:11 p.m. |
| NEDg | Description generation | batch_69c04e8422dc8190879ee52bd6850565 |
completed | March 22, 2026, 8:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c04f3963888190b1c85b3bb9ff5d44 |
completed | March 22, 2026, 8:21 p.m. |
Created at: March 22, 2026, 3:35 p.m.