Triple
T16206982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yui Rail |
E393352
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Tomigusuku |
E267202
|
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: Tomigusuku | Statement: [Yui Rail, serves, Tomigusuku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tomigusuku Context triple: [Yui Rail, serves, Tomigusuku]
-
A.
Tomigusuku
chosen
Tomigusuku is a coastal city on Japan’s Okinawa Island known for its proximity to Naha and its blend of urban development with traditional Ryukyuan culture.
-
B.
Shimotsuki
Shimotsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk in late 1944.
-
C.
Takamikura
Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
-
D.
Taketoyo
Taketoyo is a coastal town in central Japan known for its industrial facilities and location within Aichi Prefecture.
-
E.
Mitoyo
Mitoyo is a coastal city in western Kagawa Prefecture on Japan’s Shikoku Island, known for its scenic Seto Inland Sea views and rural landscapes.
- 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_69d87f1f5bd08190bd01cac0d5b9d2ef |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e227101a3c819095ef40e50bf66433 |
completed | April 17, 2026, 12:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0025f4f8708190ba1a08860e962c66 |
completed | May 10, 2026, 6:30 a.m. |
Created at: April 10, 2026, 5:03 a.m.