Triple
T14167055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 千代田区 |
E351107
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | 東京駅 |
E34204
|
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: 東京駅 | Statement: [千代田区, contains, 東京駅]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 東京駅 Context triple: [千代田区, contains, 東京駅]
-
A.
Yokohama Station
Yokohama Station is one of Japan’s busiest railway hubs, serving numerous JR, private, and subway lines in central Yokohama.
-
B.
Shinagawa Station
Shinagawa Station is a major railway and transportation hub in Tokyo, Japan, serving multiple JR and private lines as well as Shinkansen high-speed trains.
-
C.
Tokyo Station
chosen
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.
Chiba Station
Chiba Station is a major railway hub in Chiba, Japan, serving multiple JR East lines and connecting the city with the greater Tokyo metropolitan area.
-
E.
Shinjuku Station
Shinjuku Station is one of the world’s busiest railway hubs, serving as a major commercial and transportation center in Tokyo, Japan.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61b355f08190864c7322bbcb766d |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000ebbc67c8190bd930a2773edb5b2 |
completed | May 10, 2026, 4:51 a.m. |
Created at: April 10, 2026, 1 a.m.