Triple
T13316580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kintetsu Department Store |
E317202
|
entity |
| Predicate | operatesIn |
P82
|
FINISHED |
| Object | Japan |
E174
|
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: Japan | Statement: [Kintetsu Department Store, operatesIn, Japan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Japan Context triple: [Kintetsu Department Store, operatesIn, Japan]
-
A.
Japan
chosen
Japan is an East Asian island nation in the Pacific Ocean known for its advanced technology, rich cultural heritage, and major cities such as Tokyo, Osaka, and Kyoto.
-
B.
Japo
Japo is a small settlement located on Arno Atoll in the Marshall Islands.
-
C.
Ota, Japan
Ōta is a special ward in Tokyo, Japan, known for Haneda Airport, its coastal location on Tokyo Bay, and a mix of residential, industrial, and commercial districts.
-
D.
Honshu
Honshu is the largest and most populous island of Japan, home to major cities such as Tokyo, Osaka, and Kyoto.
-
E.
South Korea
South Korea is an East Asian nation on the southern half of the Korean Peninsula, known for its advanced technology, vibrant pop culture, and rapid economic development.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d990f9a384819085890e18255ee339 |
completed | April 11, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716d6dc988190ab7183089113237f |
completed | May 3, 2026, 9:35 a.m. |
Created at: April 9, 2026, 9:29 p.m.