Triple
T4007393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miebashi Station |
E89557
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Yui Rail |
E393352
|
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: Yui Rail | Statement: [Miebashi Station, partOf, Yui Rail]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yui Rail Context triple: [Miebashi Station, partOf, Yui Rail]
-
A.
Yui Rail
chosen
Yui Rail is an urban monorail system serving Naha and surrounding areas in Okinawa, Japan.
-
B.
Tsutako
Tsutako is a Japanese given name, most notably borne by Tsutako Nakasone.
-
C.
Takako
Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
-
D.
Mikoto
Mikoto is a divine title associated with the Shinto moon god Tsukuyomi, reflecting reverence and honor in Japanese mythology.
-
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_69aed9585e788190bec2d39deba3750f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa62d0e081909aaed2978a840734 |
completed | March 9, 2026, 4:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c67eddc819097eff878c860f3d5 |
completed | March 14, 2026, 11:54 a.m. |
Created at: March 9, 2026, 3:34 p.m.