Triple
T22533237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gokajō no Goseimon |
E557096
|
entity |
| Predicate | influencedBy |
P9
|
FINISHED |
| Object | rangaku |
—
|
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: rangaku | Statement: [Gokajō no Goseimon, influencedBy, rangaku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: rangaku Context triple: [Gokajō no Goseimon, influencedBy, rangaku]
-
A.
rangaku
chosen
Rangaku was the study of Western science and technology in Japan during the Edo period, based primarily on Dutch sources.
-
B.
rakuichi-rakuza
Rakuichi-rakuza was an economic policy in feudal Japan that promoted free markets and abolished monopolistic guild privileges to stimulate commerce and weaken traditional power structures.
-
C.
Karaiyamai
Karaiyamai is a locality situated within Madhesh Province in southeastern Nepal.
-
D.
Raku
Raku is a multi-paradigm, gradually typed programming language that evolved from the Perl community with a focus on expressiveness, concurrency, and powerful language features.
-
E.
Katunayake
Katunayake is a town in Sri Lanka’s Western Province known primarily as the country’s main international air gateway and an important industrial and transport hub.
- 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_69e11e57483c8190b0887c4f8ff26446 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ed88cf08190ae7e5b6bf9a80372 |
completed | April 29, 2026, 1:28 a.m. |
Created at: April 16, 2026, 8:51 p.m.