Triple
T11266920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Metro Line 17 |
E266709
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Oriental Land |
E246335
|
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: Oriental Land | Statement: [Shanghai Metro Line 17, hasStation, Oriental Land]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oriental Land Context triple: [Shanghai Metro Line 17, hasStation, Oriental Land]
-
A.
Tokyu Land Corporation
Tokyu Land Corporation is a major Japanese real estate developer and property management company within the Tokyu Group conglomerate.
-
B.
Oriental Land theme park
chosen
Oriental Land theme park is a large recreational and amusement park in Shanghai’s Qingpu District, featuring themed attractions, outdoor activities, and scenic lakeside areas.
-
C.
The Oriental Land Company
The Oriental Land Company is a Japanese leisure and tourism corporation best known for operating and licensing the Tokyo Disney Resort.
-
D.
Yomiuri Land
Yomiuri Land is a large amusement park in Inagi, Tokyo, known for its roller coasters, seasonal illuminations, and family-friendly attractions.
-
E.
Seibu Group
Seibu Group is a major Japanese conglomerate with core businesses in railways, hotels, real estate, and leisure services.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e94e5e3c8190a31995d55d20d7ed |
completed | April 9, 2026, 6 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4f4229c7081909da6b22ee6bf4905 |
completed | April 19, 2026, 3:26 p.m. |
Created at: April 8, 2026, 9:31 p.m.