Triple
T12375361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shibaura Futo |
E295109
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Shibaura |
E295109
|
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: Shibaura | Statement: [Shibaura Futo, partOf, Shibaura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shibaura Context triple: [Shibaura Futo, partOf, Shibaura]
-
A.
Shibaura Futo
chosen
Shibaura Futo is a waterfront district and pier area in Tokyo’s Minato Ward, known for its views of Tokyo Bay and proximity to the Rainbow Bridge.
-
B.
Mibuchi
Mibuchi is a Japanese surname borne by individuals such as Tadahiko Mibuchi.
-
C.
Nisshin
Nisshin is a suburban city in central Japan known for its residential communities and proximity to Nagoya in Aichi Prefecture.
-
D.
Iwaki
Iwaki is a coastal city in Fukushima Prefecture, Japan, known for its hot springs, beaches, and role as a regional commercial and industrial center.
-
E.
Shimizu
Shimizu is a prominent Japanese port city known for its busy harbor and scenic views of Mount Fuji.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93fa8ca7c8190b3f8e9c2ec23e837 |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f082b6481909950c8c4cb854440 |
completed | May 3, 2026, 10:10 a.m. |
Created at: April 8, 2026, 9:54 p.m.