Triple
T13579062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hakucho Bridge |
E324362
|
entity |
| Predicate | municipality |
P852
|
FINISHED |
| Object | Muroran City |
E1074824
|
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: Muroran City | Statement: [Hakucho Bridge, municipality, Muroran City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Muroran City Context triple: [Hakucho Bridge, municipality, Muroran City]
-
A.
Muroran
Muroran is an industrial port city in southern Hokkaido, Japan, known for its steel industry and scenic coastal landscapes.
-
B.
Muroran, Hokkaido
chosen
Muroran, Hokkaido is an industrial and port city in southern Hokkaido, Japan, known for its steel industry, coastal scenery, and role as a key maritime hub.
-
C.
Furano
Furano is a popular town in central Hokkaido, Japan, known for its scenic ski slopes in winter and vibrant lavender fields in summer.
-
D.
Kingisepp
Kingisepp is a town in northwestern Russia near the Estonian border, known for its industrial base and historical roots dating back to the 14th century.
-
E.
Iida City
Iida City is a regional city in southern Nagano Prefecture, Japan, known for its scenic mountain surroundings, traditional festivals, and agricultural products such as apples and pears.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb03052088190a2b68c106059828e |
completed | April 12, 2026, 2:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd19259070819089bd3caf66e5af29 |
completed | May 7, 2026, 10:58 p.m. |
Created at: April 9, 2026, 9:48 p.m.