Triple
T19596629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shichifukujin |
E470364
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Ebisu |
—
|
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: Ebisu | Statement: [Shichifukujin, hasMember, Ebisu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ebisu Context triple: [Shichifukujin, hasMember, Ebisu]
-
A.
Ebisu
chosen
Ebisu is a popular Japanese kami of prosperity, fishermen, and good fortune, often depicted as a cheerful, bearded man holding a fishing rod and sea bream.
-
B.
Ebisu
Ebisu is a fashionable Tokyo neighborhood known for its upscale dining, craft beer scene, and convenient access via Ebisu Station near Shibuya.
-
C.
Ebisucho
Ebisucho is a commercial and entertainment district in Osaka’s Naniwa Ward, known for its proximity to Den Den Town and its mix of electronics shops, eateries, and local businesses.
-
D.
Nisshu
Nisshu was a Buddhist disciple of the Japanese monk Nichiren, known for helping to develop and spread Nichiren Buddhism.
-
E.
Shiba
Shiba is a central district in Minato, Tokyo, known for its mix of historic temples, business centers, and residential 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e6407b997881909762c8f919c9cdad |
completed | April 20, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:43 p.m.