Triple
T11805868
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saitama Prefecture |
E280745
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Misato |
E705654
|
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: Misato | Statement: [Saitama Prefecture, hasMajorCity, Misato]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Misato Context triple: [Saitama Prefecture, hasMajorCity, Misato]
-
A.
Misato
chosen
Misato is a city located in Saitama Prefecture, Japan, known as part of the Greater Tokyo metropolitan area.
-
B.
Misato
Misato was a former municipality in Okinawa Prefecture, Japan, that was incorporated into the present-day city of Okinawa.
-
C.
Takako
Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
-
D.
Rieko Kodama
Rieko Kodama was a pioneering Japanese video game designer and producer at Sega, best known for her influential work on classic role-playing games and for being one of the first prominent women in the game industry.
-
E.
Yuriko
Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
- 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.