Triple
T9975869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tajima region |
E196325
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Yabu |
E148386
|
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: Yabu | Statement: [Tajima region, hasPart, Yabu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yabu Context triple: [Tajima region, hasPart, Yabu]
-
A.
Yabu
chosen
Yabu is a small city in northern Hyōgo Prefecture, Japan, known for its rural landscapes, hot springs, and access to mountainous outdoor recreation.
-
B.
Yabun
Yabun is a major annual Aboriginal and Torres Strait Islander cultural festival held in Sydney, celebrating Indigenous music, dance, and community.
-
C.
Oyugis
Oyugis is a town in western Kenya that serves as a key commercial and administrative center in the former Rachuonyo District of Homa Bay County.
-
D.
Yamaga
Yamaga is a historic city in Japan known for its traditional lantern festival and hot spring resorts in northern Kumamoto Prefecture.
-
E.
Kagayaki
Kagayaki is the fastest limited-stop train service operating on Japan’s Hokuriku Shinkansen line between Tokyo and the Hokuriku region.
- 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_69ca82eea2b88190a0e511d21a31f386 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb84b47308190aa2f94fa7320cdc3 |
completed | April 2, 2026, 12:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dbd9073c948190aa2e9e6b7ffe9022 |
completed | April 12, 2026, 5:40 p.m. |
Created at: March 30, 2026, 8:48 p.m.