Triple
T1882630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Namba Parks |
E39886
|
entity |
| Predicate | neighborhood |
P988
|
FINISHED |
| Object | Namba |
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 | Statement: [Namba Parks, neighborhood, Namba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Namba Context triple: [Namba Parks, neighborhood, Namba]
-
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.
Numata
Numata is a city in Gunma Prefecture, Japan, known as a gateway to the Mount Akagi and Oze National Park areas.
-
C.
Kanuma
Kanuma is a regional harvest festival celebrated mainly in Andhra Pradesh and Telangana as part of the multi-day Makar Sankranti festivities, focusing on cattle worship and agricultural prosperity.
-
D.
Sannomiya
Sannomiya is a major commercial and transportation hub in central Kobe, Japan, known for its shopping streets, nightlife, and role as the city’s downtown core.
-
E.
Namaka
Namaka is the smaller and inner of the two known moons orbiting the dwarf planet Haumea in the Kuiper Belt.
- 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_69a88633e4fc8190b7eb40463e048ec5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0fd4d6881908b8266bdae1517ce |
completed | March 7, 2026, 5 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeae631488190b5b4a8137112e568 |
completed | March 8, 2026, 9:32 p.m. |
Created at: March 4, 2026, 7:34 p.m.