Triple
T14345564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaoru |
E355708
|
entity |
| Predicate | inLoveWith |
P7325
|
FINISHED |
| Object | Ukifune |
—
|
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: Ukifune | Statement: [Kaoru, inLoveWith, Ukifune]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ukifune Context triple: [Kaoru, inLoveWith, Ukifune]
-
A.
Ukiha
Ukiha is a small city in southwestern Japan known for its rural landscapes, fruit orchards, and traditional townscapes.
-
B.
Shimotsuki
Shimotsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk in late 1944.
-
C.
Takamikura
Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
-
D.
Fujitsubo
chosen
Fujitsubo is a noblewoman in "The Tale of Genji," renowned as Hikaru Genji’s stepmother and forbidden love, whose resemblance to his mother drives much of the novel’s central emotional and moral conflict.
-
E.
Furubira
Furubira is a small coastal town in Hokkaido, Japan, known for its fishing industry and scenic seaside landscapes.
- 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_69d82790a7e08190877e2d349b2e8d8e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8e8b81bc8190ace2a575faf55cc0 |
completed | April 14, 2026, 6:59 p.m. |
Created at: April 10, 2026, 1:14 a.m.