Triple
T4419590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shuri Station |
E95063
|
entity |
| Predicate | servedBy |
P82
|
FINISHED |
| Object | Okinawa Urban Monorail |
E93549
|
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: Okinawa Urban Monorail | Statement: [Shuri Station, servedBy, Okinawa Urban Monorail]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Okinawa Urban Monorail Context triple: [Shuri Station, servedBy, Okinawa Urban Monorail]
-
A.
Okinawa Urban Monorail
chosen
Okinawa Urban Monorail is an elevated rail transit system serving the city of Naha and surrounding areas on Japan’s Okinawa Island.
-
B.
Osaka Monorail
Osaka Monorail is a straddle-beam monorail system in Osaka Prefecture, Japan, serving as a major urban transit line linking key suburbs, commercial areas, and transport hubs.
-
C.
Tokyo Monorail
Tokyo Monorail is an urban transit line in Tokyo that provides rapid rail service between central Tokyo and Haneda Airport.
-
D.
Tama Monorail
Tama Monorail is a straddle-beam monorail line in Tokyo, Japan, providing urban transit service through the Tama area.
-
E.
KL Monorail
KL Monorail is an elevated urban rail line in Kuala Lumpur that provides rapid transit service through the city’s central and commercial districts.
- 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_69b3453a36908190b95a79a297ca083c |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3551fae7c8190abafda0d78f02d89 |
completed | March 13, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6374ffbd081908c96847ec2d25cee |
completed | March 15, 2026, 4:36 a.m. |
Created at: March 12, 2026, 11:29 p.m.