Triple
T13692112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | N700 series Shinkansen |
E328290
|
entity |
| Predicate | serviceType |
P87
|
FINISHED |
| Object | Tsubame |
E389801
|
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: Tsubame | Statement: [N700 series Shinkansen, serviceType, Tsubame]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tsubame Context triple: [N700 series Shinkansen, serviceType, Tsubame]
-
A.
Tsubame
chosen
Tsubame is a Japanese Shinkansen train service that operates on the Kyushu Shinkansen line in southern Japan.
-
B.
Tsuru
Tsuru is a small city in Yamanashi Prefecture, Japan, known for its scenic setting near Mount Fuji and its educational institutions.
-
C.
Murai
Murai is a Japanese surname borne by various notable individuals across fields such as film, music, and sports.
-
D.
Akahige
Akahige is the Japanese name for the Japanese robin, a small passerine bird native to East Asia known for its bright orange-red face and breast.
-
E.
Hamachō
Hamachō is a neighborhood in Chūō ward, central Tokyo, known for its mix of residential areas, local businesses, and proximity to the Nihonbashi district.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc8746458819095ec1ba3c01ef31b |
completed | April 12, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d4c52fc8190a93d05c24a8d1513 |
completed | May 3, 2026, 7:09 p.m. |
Created at: April 9, 2026, 9:53 p.m.