Triple
T11862482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shōken Kōtaigō |
E282192
|
entity |
| Predicate | honorificTitle |
P2097
|
FINISHED |
| Object | Kōtaigō |
E265360
|
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: Kōtaigō | Statement: [Shōken Kōtaigō, honorificTitle, Kōtaigō]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kōtaigō Context triple: [Shōken Kōtaigō, honorificTitle, Kōtaigō]
-
A.
Koshigaya
Koshigaya is a suburban city in Japan known for its large shopping complexes and residential communities within the Greater Tokyo metropolitan area.
-
B.
Kōta
Kōta is a town in central Japan known for its manufacturing industries and location within Aichi Prefecture.
-
C.
Kyotanabe
Kyotanabe is a city in Kyoto Prefecture, Japan, known for its residential suburbs, educational institutions, and location within the Kansai region.
-
D.
Kōgō
chosen
Kōgō is the Japanese term used to refer to the empress consort of Japan.
-
E.
Shibukawa
Shibukawa is a city in Gunma Prefecture, Japan, known as a regional transport hub and gateway to nearby hot spring resorts such as Ikaho Onsen.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a69b16bc8190999a0c1240f9ce6a |
completed | April 10, 2026, 7:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f3548b48190aec852723654bd35 |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 8, 2026, 9:43 p.m.