Triple
T19009821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shōhō |
E465190
|
entity |
| Predicate | precededBy |
P97
|
FINISHED |
| Object | Kan'ei |
—
|
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: Kan'ei | Statement: [Shōhō, precededBy, Kan'ei]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kan'ei Context triple: [Shōhō, precededBy, Kan'ei]
-
A.
Kan'ei
chosen
Kan'ei was a Japanese era name (nengō) of the early Edo period, notable for political consolidation under the Tokugawa shogunate and significant cultural development.
-
B.
Kanramachi
Kanramachi is a Japanese town known for its cultural and municipal partnership with the Italian town of Certaldo.
-
C.
Nishi-Tobecho
Nishi-Tobecho is a notable neighborhood within Nishi Ward in Yokohama, Japan, known as part of the city’s central urban area.
-
D.
Tawaramachi
Tawaramachi is a neighborhood in Tokyo, Japan, known for its traditional downtown atmosphere and proximity to the historic Asakusa district.
-
E.
Haginochaya
Haginochaya is a neighborhood in Osaka’s Naniwa Ward known for its dense urban streetscape, budget accommodations, and proximity to major transit and entertainment areas.
- 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_69d8dd025c188190a1d81f5b4ec7e2c6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6a8225c81908e80ae7eb1c1301b |
completed | April 20, 2026, 7:32 a.m. |
Created at: April 10, 2026, 12:02 p.m.