Triple
T6322227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miyagi Prefecture |
E141769
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Sendai Station |
E498821
|
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: Sendai Station | Statement: [Miyagi Prefecture, contains, Sendai Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sendai Station Context triple: [Miyagi Prefecture, contains, Sendai Station]
-
A.
Sendai Station
chosen
Sendai Station is the main railway hub of Sendai, Japan, serving as a major stop for Shinkansen high-speed trains and numerous local and regional lines.
-
B.
Nagoya Station
Nagoya Station is one of Japan’s largest and busiest railway hubs, serving as a major Shinkansen and regional transit center in the city of Nagoya.
-
C.
Daigo Station
Daigo Station is a subway station in Kyoto, Japan, serving the Kyoto Municipal Subway network and providing access to the Daigo area and nearby cultural sites.
-
D.
Nagano Station
Nagano Station is a major railway hub in Nagano, Japan, serving as a gateway to the region’s ski resorts, temples, and surrounding mountain areas.
-
E.
Yokohama Station
Yokohama Station is one of Japan’s busiest railway hubs, serving numerous JR, private, and subway lines in central Yokohama.
- 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_69c008d13b8c8190be47d896eb735605 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c064c76dfc8190a1d44fd0c4402a0e |
completed | March 22, 2026, 9:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea7b9d020819091342951d00661f9 |
completed | April 2, 2026, 5:30 p.m. |
Created at: March 22, 2026, 4:29 p.m.