Triple
T6083504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fukuchiyama |
E135578
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Ayabe |
E319177
|
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: Ayabe | Statement: [Fukuchiyama, borders, Ayabe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ayabe Context triple: [Fukuchiyama, borders, Ayabe]
-
A.
Ayabe
chosen
Ayabe is a small city in the northern part of Japan’s Kyoto Prefecture, known for its rural landscapes, traditional industries, and spiritual retreat centers.
-
B.
Fujieda
Fujieda is a city in Shizuoka Prefecture, Japan, known as a regional commercial center with a mix of residential areas, agriculture, and light industry.
-
C.
Yawata
Yawata is a city in Japan known for its historic Iwashimizu Hachimangū Shrine and its location in the southern part of Kyoto Prefecture.
-
D.
Toyokawa
Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
-
E.
Ichinomiya
Ichinomiya is a city in Aichi Prefecture, Japan, known historically as a textile and commercial center within the Nagoya metropolitan area.
- 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_69c0087bcc788190b20f093d3a6c60ec |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057877b448190aa12d2484102eeaa |
completed | March 22, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d100a1ad688190b1a2fc91ce3dbdc3 |
completed | April 4, 2026, 12:14 p.m. |
Created at: March 22, 2026, 4:11 p.m.