Triple
T14064063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nihombashi district |
E338416
|
entity |
| Predicate | hasOfficialNameInJapanese |
P9882
|
FINISHED |
| Object | 日本橋 |
E565231
|
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: 日本橋 | Statement: [Nihombashi district, hasOfficialNameInJapanese, 日本橋]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 日本橋 Context triple: [Nihombashi district, hasOfficialNameInJapanese, 日本橋]
-
A.
五条大橋
五条大橋 is a historic bridge in Kyoto, Japan, best known as the legendary site of the encounter between the warrior monk Benkei and the folk hero Minamoto no Yoshitsune.
-
B.
Nijūbashi Bridge
Nijūbashi Bridge is a famous pair of arched bridges at the main entrance to Tokyo’s Imperial Palace, known as one of Japan’s most iconic and photographed landmarks.
-
C.
Nihonbashi Bridge
chosen
Nihonbashi Bridge is a historic stone arch bridge in central Tokyo that has long served as Japan’s traditional kilometer zero and a key commercial and cultural landmark.
-
D.
伊良部大橋
伊良部大橋は、沖縄県宮古島と伊良部島を結ぶ日本有数の長さを誇る無料の海上橋です。
-
E.
Nipponbashi
Nipponbashi is a district in Osaka, Japan, known for its electronics shops, anime and manga stores, and otaku culture, often compared to Tokyo’s Akihabara.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5689c7f48190a47ca94eaa8a9ef9 |
completed | April 14, 2026, 3 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcb6673de881909653c7691422b800 |
completed | May 7, 2026, 3:57 p.m. |
Created at: April 9, 2026, 10:21 p.m.