Triple
T19628902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rokkasen |
E471212
|
entity |
| Predicate | hasNotableMember |
P304
|
FINISHED |
| Object | Kisen Hōshi |
—
|
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: Kisen Hōshi | Statement: [Rokkasen, hasNotableMember, Kisen Hōshi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kisen Hōshi Context triple: [Rokkasen, hasNotableMember, Kisen Hōshi]
-
A.
Kisen Hōshi
chosen
Kisen Hōshi was a Heian-period Japanese Buddhist monk and poet renowned as one of the Six Poetic Immortals (Rokkasen).
-
B.
Shizumanu Taiyō
Shizumanu Taiyō is a Japanese drama film, based on Toyoko Yamasaki’s novel, that explores corporate corruption and personal integrity within a national airline.
-
C.
Seishi
Seishi is a Japanese given name historically borne by figures such as Fujiwara no Seishi, a noblewoman of the Heian period.
-
D.
Rokusei
Rokusei is a Japanese tokusatsu superhero team that succeeds Gosei in the narrative sequence of its series.
-
E.
Koshun
Koshun is a music producer known for working on projects associated with the artist Amala.
- 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_69d8e511f28481909f4bc3ea9191e54a |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e641007e5881908da78e50aa36f340 |
completed | April 20, 2026, 3:06 p.m. |
Created at: April 10, 2026, 1:44 p.m.