Triple
T11876961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | うめだスカイビル |
E282551
|
entity |
| Predicate | 都市景観への影響 |
P102013
|
FINISHED |
| Object | 大阪のスカイラインを代表する建物の一つ |
—
|
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: 大阪のスカイラインを代表する建物の一つ | Statement: [うめだスカイビル, 都市景観への影響, 大阪のスカイラインを代表する建物の一つ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 都市景観への影響 Context triple: [うめだスカイビル, 都市景観への影響, 大阪のスカイラインを代表する建物の一つ]
-
A.
cityView
Indicates that one entity offers a view of, or overlooks, a city.
-
B.
urbanDesign
Indicates the relationship in which an entity is responsible for planning, organizing, or shaping the physical layout and functional structure of urban spaces.
-
C.
hasTourismImpactOn
Indicates that one entity affects or influences the tourism levels, patterns, or attractiveness of another entity.
-
D.
cityOverlooks
Indicates that a city has a direct visual view over or across a particular geographic feature, area, or landmark.
-
E.
urbanMorphology
Indicates the spatial form, structure, and layout relationships that characterize the physical configuration of an urban area.
- F. None of above. chosen
Provenance (4 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d39d2934819093b9f7006f45e5cb |
completed | April 10, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69d8bb272f88819090c37c944c5a60ab |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8d399d58c81908dab572aa82426d7 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 8, 2026, 9:44 p.m.