Triple
T14016706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 六甲アイランド |
E337221
|
entity |
| Predicate | ランドマーク的要素 |
P37670
|
FINISHED |
| Object | 海に囲まれた景観 |
—
|
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: 海に囲まれた景観 | Statement: [六甲アイランド, ランドマーク的要素, 海に囲まれた景観]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ランドマーク的要素 Context triple: [六甲アイランド, ランドマーク的要素, 海に囲まれた景観]
-
A.
相关城市地标
Indicates a relationship where a city landmark is associated with, connected to, or relevant to a given entity or context.
-
B.
includesLandmark
Indicates that one location or area contains or encompasses a specific landmark within its boundaries.
-
C.
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.
-
D.
iconicFeature
chosen
Indicates that something serves as a distinctive, widely recognized characteristic or symbol of another entity.
-
E.
emblematicBuildingLocation
Indicates that a building serves as a symbolic or representative landmark for a particular location or area.
- 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2f396b648190927e5718c3bb6511 |
completed | April 14, 2026, 12:12 p.m. |
| PD | Predicate disambiguation | batch_69de05a802ac819090604025aae6a4d5 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:19 p.m.