Triple
T4590483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nishi-ku, Yokohama |
E103473
|
entity |
| Predicate | hasMajorRailHub |
P1071
|
FINISHED |
| Object | Yokohama Station |
E403108
|
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: Yokohama Station | Statement: [Nishi-ku, Yokohama, hasMajorRailHub, Yokohama Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yokohama Station Context triple: [Nishi-ku, Yokohama, hasMajorRailHub, Yokohama Station]
-
A.
Yokohama Station
chosen
Yokohama Station is one of Japan’s busiest railway hubs, serving numerous JR, private, and subway lines in central Yokohama.
-
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.
Tokyo Station
Tokyo Station is a major railway hub in central Tokyo, serving as a key terminal for Shinkansen bullet trains and numerous local and regional lines.
-
D.
Suita Station
Suita Station is a railway station in Suita, Osaka Prefecture, Japan, serving passengers on the JR Kyoto Line (Tōkaidō Main Line).
-
E.
Sendai Station
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.
- 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_69bd43dccaf08190aa89e9991a289719 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5923c0c88190952137d448d474cf |
completed | March 20, 2026, 2:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8de86454081909232f45fa7d48976 |
completed | March 29, 2026, 8:10 a.m. |
Created at: March 20, 2026, 1:11 p.m.