Triple
T16591872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yokohama Station |
E403108
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | Keikyū |
—
|
NE NERFINISHED |
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: Keikyū | Statement: [Yokohama Station, operator, Keikyū]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Keikyū Context triple: [Yokohama Station, operator, Keikyū]
-
A.
Keikyū
chosen
Keikyū is a major private railway operator in the Greater Tokyo area of Japan, known for its commuter and airport rail services.
-
B.
Ibukijima
Ibukijima is a small island in Japan’s Seto Inland Sea known for its fishing community and role as a contemporary art site in the Setouchi region.
-
C.
Suō-Ōshima
Suō-Ōshima is a large inhabited island in Japan’s Seto Inland Sea known for its scenic coastal landscapes, citrus cultivation, and cultural ties with Hawaii.
-
D.
Mukōjima
Mukōjima is a neighborhood in Tokyo’s Sumida ward known for its traditional atmosphere, historic geisha district, and riverside cherry blossom viewing along the Sumida River.
-
E.
Tsukishima
Tsukishima is a man-made island and residential district in Tokyo’s Chūō ward, known for its high-rise apartments and famous monjayaki restaurants.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d88387363c8190a97a0c942130de97 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e359a123e8819095cd73cd848a3345 |
completed | April 18, 2026, 10:14 a.m. |
Created at: April 10, 2026, 5:16 a.m.