Triple
T15399847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Kantō urban area |
E368282
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Mito |
E300703
|
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: Mito | Statement: [Northern Kantō urban area, hasMajorCity, Mito]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mito Context triple: [Northern Kantō urban area, hasMajorCity, Mito]
-
A.
Mito
chosen
Mito is the capital city of Ibaraki Prefecture in Japan’s Kantō region, known for its historic Kairakuen Garden and cultural heritage.
-
B.
Mijas
Mijas is a picturesque municipality in the province of Málaga in southern Spain, known for its whitewashed village, coastal resorts, and location along the Costa del Sol.
-
C.
Eusa
Eusa is the Breton name for Ushant, an island off the western tip of Brittany in France known for its rugged coastline and maritime heritage.
-
D.
Mitino
Mitino is a Moscow Metro station serving the Mitino District in the northwestern part of the city.
-
E.
Moru
Moru is a Central Sudanic language spoken primarily by the Moru people in South Sudan.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e8d89e08190b7cae778d89fb5e1 |
completed | April 16, 2026, 1:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff13567e3481908eb6293c6af35f3a |
completed | May 9, 2026, 10:58 a.m. |
Created at: April 10, 2026, 3:19 a.m.