Triple
T5667895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Etajima Island |
E124900
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Hiroshima |
E29708
|
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: Hiroshima | Statement: [Etajima Island, hasNearbyCity, Hiroshima]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hiroshima Context triple: [Etajima Island, hasNearbyCity, Hiroshima]
-
A.
Hiroshima
chosen
Hiroshima is a Japanese city on Honshu Island internationally known as the first place in history to be devastated by an atomic bomb during World War II.
-
B.
Nagasaki
Nagasaki is a major port city in southwestern Japan historically known as one of the two cities devastated by an American atomic bomb during World War II.
-
C.
Sendai
Sendai is the largest city in Japan’s Tōhoku region, known for its lush greenery, historic sites, and status as a major economic and cultural center in northeastern Honshu.
-
D.
Minamata
Minamata is a powerful photo-essay and book by W. Eugene Smith documenting the devastating effects of industrial mercury poisoning on a Japanese fishing community.
-
E.
Toyokawa
Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
- 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_69c00828906881908966f270b8f130cf |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c023471f688190acec330596238a50 |
completed | March 22, 2026, 5:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a2b38c88190bdd0e172644df081 |
completed | March 22, 2026, 9:07 p.m. |
Created at: March 22, 2026, 3:43 p.m.