Triple
T18290079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Y2 |
E438086
|
entity |
| Predicate | servesCity |
P82
|
FINISHED |
| Object | Naha |
—
|
NE NERFINISHED |
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: Naha | Statement: [Y2, servesCity, Naha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naha Context triple: [Y2, servesCity, Naha]
-
A.
Naha
chosen
Naha is the capital and largest city of Okinawa Prefecture in Japan, known as a major political, economic, and cultural center of the Ryukyu Islands.
-
B.
Nago
Nago is a coastal city in northern Okinawa, Japan, known for its beaches, subtropical climate, and role as a regional commercial and cultural center.
-
C.
Naha City
Naha City is the capital of Okinawa Prefecture in Japan, known for its rich Ryukyuan cultural heritage, historic sites, and vibrant urban center.
-
D.
Nhava
Nhava is a coastal village in Navi Mumbai, Maharashtra, India, situated near the Jawaharlal Nehru Port (Nhava Sheva) and known historically for its fishing community and maritime connections.
-
E.
Hanam
Hanam is a city in South Korea known for its rapid urban development and large shopping and residential complexes, located just east of Seoul in Gyeonggi Province.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e500fd65888190afdbb29dc60066af |
completed | April 19, 2026, 4:21 p.m. |
Created at: April 10, 2026, 10:35 a.m.