Triple
T16992855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iga Province |
E412235
|
entity |
| Predicate | hasNotableCity |
P2813
|
FINISHED |
| Object | Ueno (Iga Ueno) |
E526493
|
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: Ueno (Iga Ueno) | Statement: [Iga Province, hasNotableCity, Ueno (Iga Ueno)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ueno (Iga Ueno) Context triple: [Iga Province, hasNotableCity, Ueno (Iga Ueno)]
-
A.
Ōyodo
Ōyodo was a Japanese light cruiser of the Imperial Japanese Navy in World War II, designed as a flagship for submarine operations and later used in major Pacific naval engagements.
-
B.
Kanramachi
Kanramachi is a Japanese town known for its cultural and municipal partnership with the Italian town of Certaldo.
-
C.
Ueno
Ueno is a major district in Tokyo known for Ueno Park, its museums, zoo, and busy transportation hub.
-
D.
Ueno
chosen
Ueno is a town in Japan historically known as the birthplace of the renowned haiku poet Matsuo Bashō.
-
E.
Kudamatsu
Kudamatsu is a coastal city in western Japan known for its industrial facilities and location along the Seto Inland Sea in Yamaguchi Prefecture.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d283d2388190a78bf8d179e83fdc |
completed | April 18, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00dc16fbdc819095411a056b9942c3 |
completed | May 10, 2026, 7:27 p.m. |
Created at: April 10, 2026, 5:32 a.m.