Triple
T514533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yokohama |
E10676
|
entity |
| Predicate | hasWard |
P14475
|
FINISHED |
| Object | Minato Mirai area |
E103473
|
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: Minato Mirai area | Statement: [Yokohama, hasWard, Minato Mirai area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Minato Mirai area Context triple: [Yokohama, hasWard, Minato Mirai area]
-
A.
Minato
Minato is a central special ward of Tokyo known for its major business districts, foreign embassies, and landmarks such as Tokyo Tower and Roppongi.
-
B.
Minato-ku
Minato-ku is a central ward of Osaka, Japan, known for its waterfront attractions and major landmarks such as the Osaka Aquarium Kaiyukan.
-
C.
Nishi-ku
chosen
Nishi-ku is a central ward of Yokohama, Japan, known as a major commercial and business district that includes the Minato Mirai 21 waterfront area.
-
D.
Toyonaka
Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
-
E.
Umeda district
Umeda district is a major commercial and transportation hub in Osaka, Japan, known for its skyscrapers, shopping complexes, and extensive train and subway connections.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f3b7557c8190a29cf1de359ea2ea |
completed | Feb. 28, 2026, 1:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c000b64c819091140b7c3718acf6 |
completed | March 4, 2026, 5:15 a.m. |
Created at: Feb. 28, 2026, 1:12 p.m.