Triple
T19287235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nishi Amane |
E482345
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Nishi |
—
|
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: Nishi | Statement: [Nishi Amane, familyName, Nishi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nishi Context triple: [Nishi Amane, familyName, Nishi]
-
A.
Nishi
chosen
Nishi is a Japanese surname borne by various notable figures in fields such as philosophy, politics, and the arts.
-
B.
Nagahori
Nagahori is a district in Osaka, Japan, known primarily as an urban area served by the Osaka Metro Nagahori Tsurumi-ryokuchi Line.
-
C.
Nishiwaki
Nishiwaki is a city in central Hyōgo Prefecture, Japan, known for its location near the geographic center of the country and its mix of industrial and rural landscapes.
-
D.
Tsuwano
Tsuwano is a historic castle town in Shimane Prefecture, Japan, known for its preserved samurai residences, traditional streetscapes, and cultural heritage.
-
E.
Nishio
Nishio is a city in Aichi Prefecture, Japan, known for its high-quality matcha green tea production and traditional Japanese culture.
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc032f108190a89e47d1458f3f55 |
completed | April 20, 2026, 10:12 a.m. |
Created at: April 10, 2026, 1:30 p.m.