Triple
T15109650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sunshine 60 Observatory |
E360876
|
entity |
| Predicate | hasViewOfLandmark |
P9193
|
FINISHED |
| Object | Shinjuku skyscraper district (distant view) |
—
|
LITERAL 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: Shinjuku skyscraper district (distant view) | Statement: [Sunshine 60 Observatory, hasViewOfLandmark, Shinjuku skyscraper district (distant view)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasViewOfLandmark Context triple: [Sunshine 60 Observatory, hasViewOfLandmark, Shinjuku skyscraper district (distant view)]
-
A.
hasScenicViewOf
chosen
Indicates that one entity offers a visually appealing or picturesque view of another entity.
-
B.
isLandmarkFor
Indicates that one entity serves as a notable or significant reference point or attraction for another entity, such as a place, route, or area.
-
C.
includesLandmark
Indicates that one location or area contains or encompasses a specific landmark within its boundaries.
-
D.
hasSights
Indicates that an entity possesses or features notable sights, attractions, or points of interest.
-
E.
hasLandmarkProperty
Indicates that something possesses a notable or defining landmark-related characteristic or feature.
- F. None of above.
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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0058c04f481909deeac0271d961b6 |
completed | April 15, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69deb96c1d9c81909351558ed97bc5b7 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:05 a.m.