Triple
T11805871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saitama Prefecture |
E280745
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Shiki |
E717837
|
NE FINISHED |
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: Shiki | Statement: [Saitama Prefecture, hasMajorCity, Shiki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shiki Context triple: [Saitama Prefecture, hasMajorCity, Shiki]
-
A.
Shiki
chosen
Shiki is a city in Saitama Prefecture, Japan, known as a residential and commercial hub within the Greater Tokyo metropolitan area.
-
B.
Aishō
Aishō is a town in Shiga Prefecture, Japan, known for its rural character and historical sites.
-
C.
Shinsekai
Shinsekai is a retro entertainment district in Osaka, Japan, known for its nostalgic Showa-era atmosphere, street food, and neon-lit nightlife.
-
D.
Katsuragi
Katsuragi was a late-war Imperial Japanese Navy aircraft carrier that served in the Pacific Theater during World War II.
-
E.
Katsuragi
Katsuragi is a city in Japan known for its location in Nara Prefecture and its historical and cultural ties to the ancient Yamato region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6ab26aae88190b2489efcb2a24234 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5c8324481909a54852a9bb714e0 |
completed | April 10, 2026, 7:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f28110623481908354bdd4e437f99e |
completed | April 29, 2026, 10:07 p.m. |
Created at: April 8, 2026, 9:42 p.m.