Triple
T10238911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emperor Nintoku |
E243537
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Namba (traditional attribution) |
E4490
|
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: Namba (traditional attribution) | Statement: [Emperor Nintoku, capital, Namba (traditional attribution)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Namba (traditional attribution) Context triple: [Emperor Nintoku, capital, Namba (traditional attribution)]
-
A.
Namba
chosen
Namba is a major commercial and entertainment district in Osaka, Japan, known for its bustling nightlife, shopping, and iconic neon-lit streets.
-
B.
Gonnoi (traditional attribution)
Gonnoi (traditional attribution) is an ancient town in Thessaly, Greece, traditionally regarded by some sources as the birthplace of the Hellenistic ruler Antigonus I Monophthalmus.
-
C.
Namo
Namo is a small settlement on the remote Polynesian outlier atoll of Sikaiana in the Solomon Islands.
-
D.
Namu
Namu is the main settlement and administrative center of Namu Atoll in the Marshall Islands.
-
E.
Namanve
Namanve is an industrial and commercial area in central Uganda known for hosting the Kampala Industrial and Business Park and various manufacturing facilities.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d21ca3008190bfbde4074b37592d |
completed | April 7, 2026, 9:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f776464881908957e1ac4b49d936 |
completed | April 9, 2026, 12:48 a.m. |
Created at: April 6, 2026, 11:23 a.m.