Triple
T17759772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanyo Main Line |
E443338
|
entity |
| Predicate | connectsCity |
P4245
|
FINISHED |
| Object | Iwakuni |
—
|
NE NERFINISHED |
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: Iwakuni | Statement: [Sanyo Main Line, connectsCity, Iwakuni]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Iwakuni Context triple: [Sanyo Main Line, connectsCity, Iwakuni]
-
A.
Iwakuni
chosen
Iwakuni is a historic city in western Japan known for its iconic wooden Kintai Bridge and its location along the Nishiki River.
-
B.
Yorinaga
Yorinaga is a Japanese given name most notably borne by the Heian-period court noble Fujiwara no Yorinaga.
-
C.
Hiranaka
Hiranaka is a Japanese surname borne by individuals such as former professional boxer Akinobu Hiranaka.
-
D.
Takaishi
Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
-
E.
Wakatsuki
Wakatsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk during late-war Pacific naval operations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48421c3048190b26864b72aad0d70 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 10:10 a.m.