Triple
T15024246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokoro |
E378166
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Kitami |
E1048107
|
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: Kitami | Statement: [Tokoro, locatedIn, Kitami]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kitami Context triple: [Tokoro, locatedIn, Kitami]
-
A.
Kitami
Kitami is a city in northeastern Hokkaido, Japan, known for its cold winters, onion production, and proximity to the Okhotsk Sea.
-
B.
Kitakami
Kitakami is a city in northeastern Japan known for its scenic river valley, cherry blossoms, and role as a regional industrial and transportation hub.
-
C.
Kitami, Hokkaido
chosen
Kitami is a city in northeastern Hokkaido, Japan, known as a regional commercial center and gateway to the Okhotsk area.
-
D.
Yuzawa
Yuzawa is a Japanese city best known for its hot springs and ski resorts, making it a popular winter tourism destination.
-
E.
Shizunai
Shizunai was a former town in Hokkaido, Japan, known for its horse-breeding traditions and later incorporated into the town of Shinhidaka.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7de117c8190a1b9fa8d1602057e |
completed | April 15, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fea5b0bbf4819082e14715bfd6003d |
completed | May 9, 2026, 3:10 a.m. |
Created at: April 10, 2026, 2:56 a.m.