Triple
T17759775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanyo Main Line |
E443338
|
entity |
| Predicate | connectsCity |
P4245
|
FINISHED |
| Object | Hofu |
—
|
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: Hofu | Statement: [Sanyo Main Line, connectsCity, Hofu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hofu Context triple: [Sanyo Main Line, connectsCity, Hofu]
-
A.
Hofu
Hofu is a coastal city in western Honshu, Japan, known for its historic Hofu Tenmangu Shrine and industrial manufacturing base.
-
B.
Hōfu
chosen
Hōfu is a city in Yamaguchi Prefecture, Japan, known historically as the birthplace of influential Meiji-era statesman Itō Hirobumi.
-
C.
Fukutsu
Fukutsu is a coastal city in southwestern Japan known for its beaches and location along the Genkai Sea in Fukuoka Prefecture.
-
D.
Takasago
Takasago is a classic Noh play, traditionally attributed to Zeami Motokiyo, that centers on an elderly couple symbolizing marital harmony and the unity of past and present.
-
E.
Nonoichi
Nonoichi is a city in Ishikawa Prefecture, Japan, known for its residential character and proximity to the regional hub of Kanazawa.
- 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.