Triple
T15764080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toya caldera |
E382173
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Muroran |
E80590
|
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 | Statement: [Toya caldera, hasNearbyCity, Muroran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Muroran Context triple: [Toya caldera, hasNearbyCity, Muroran]
-
A.
Muroran
chosen
Muroran is an industrial port city in southern Hokkaido, Japan, known for its steel industry and scenic coastal landscapes.
-
B.
Kalyazin
Kalyazin is a historic town in Tver Oblast, Russia, known for its partially submerged bell tower in the Uglich Reservoir.
-
C.
Uglich
Uglich is a historic Russian town on the Volga River, known for its medieval architecture and its association with the mysterious death of Tsarevich Dmitry in 1591.
-
D.
Soligorsk
Soligorsk is an industrial city in Belarus known for its large potash mining operations and location in the southern part of the Minsk Region.
-
E.
Odintsovo
Odintsovo is a town in western Russia that serves as an important suburban center just outside Moscow.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b6c9fc8190a1bcf763c4b04b12 |
completed | April 16, 2026, 3 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa9361f5c8190b68702154d05bbc2 |
completed | May 9, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:47 a.m.