Triple
T20920355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bungo Province |
E515189
|
entity |
| Predicate | hasNotablePort |
P6498
|
FINISHED |
| Object | Funai |
—
|
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: Funai | Statement: [Bungo Province, hasNotablePort, Funai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Funai Context triple: [Bungo Province, hasNotablePort, Funai]
-
A.
Funai
chosen
Funai was the historical castle town that served as the political and administrative center of Japan’s former Bungo Province on Kyushu.
-
B.
Funaki
Funaki is a Japanese surname most notably associated with Olympic gold medal-winning ski jumper Kazuyoshi Funaki.
-
C.
Nimco
Nimco is the wife of Somali-born British journalist and television news presenter Rageh Omaar.
-
D.
Kachidoki
Kachidoki is a waterfront district in Tokyo’s Chūō ward known for its high-rise residential towers, proximity to the Sumida River, and convenient access to central Tokyo.
-
E.
Sanyo-Onoda
Sanyo-Onoda is a coastal industrial city in western Japan known for its cement and chemical industries and its location along the Seto Inland Sea.
- 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_69e0b4f9d5ec8190bb2bd27350ed341c |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6ec677338819081410cbaa2846260 |
completed | April 21, 2026, 3:17 a.m. |
Created at: April 16, 2026, 12:48 p.m.