Triple
T18613757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shinagawa Station area |
E454964
|
entity |
| Predicate | nearbyArea |
P2064
|
FINISHED |
| Object | Takanawa |
—
|
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: Takanawa | Statement: [Shinagawa Station area, nearbyArea, Takanawa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Takanawa Context triple: [Shinagawa Station area, nearbyArea, Takanawa]
-
A.
Takanawa
chosen
Takanawa is an upscale residential and commercial district in Minato, Tokyo, known for its luxury hotels, embassies, and proximity to major transport hubs like Shinagawa Station.
-
B.
Tamagawa
Tamagawa is the romanized Japanese name for the Tama River, a major river flowing through the Tokyo metropolitan area.
-
C.
Tanimachi
Tanimachi is a central district in Osaka, Japan, known for its mix of government offices, historic temples, and urban residential and commercial areas.
-
D.
Kitashinagawa
Kitashinagawa is a neighborhood in Tokyo’s Shinagawa ward known for its traditional shopping streets, historic temples, and proximity to Shinagawa Station.
-
E.
Nijūbashi
Nijūbashi is the iconic pair of bridges at the main entrance to Tokyo's Imperial Palace, famous for their elegant arches reflected in the surrounding moat.
- 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_69d8d38bbe7c8190bdec3138e7d413c9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54d03feb88190bbd8889273d82f7f |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 10, 2026, 11:45 a.m.