Triple
T25399959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 大阪城 |
E636391
|
entity |
| Predicate | 観光上の特徴 |
P84159
|
FINISHED |
| Object | 紅葉の名所 |
—
|
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: 紅葉の名所 | Statement: [大阪城, 観光上の特徴, 紅葉の名所]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 観光上の特徴 Context triple: [大阪城, 観光上の特徴, 紅葉の名所]
-
A.
tourismCharacteristic
chosen
Indicates that something has a specific feature, quality, or attribute relevant to tourism, such as what makes a place, service, or activity notable or suitable for tourists.
-
B.
tourismFeature
Indicates that something serves as an attraction, amenity, or point of interest relevant to tourism or visitors.
-
C.
travelCharacteristic
Indicates a quality, feature, or attribute that characterizes how travel or movement is conducted or experienced.
-
D.
notableFeatureOn
Indicates that one entity is a prominent or distinguishing feature located on or part of another entity.
-
E.
notableLocationFeature
Indicates that a location is characterized or distinguished by a particular notable physical or contextual 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_69e75db263888190b77fff9e2827b9a2 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f584f978a881909842e36f61b9a40a |
completed | May 2, 2026, 5 a.m. |
| PD | Predicate disambiguation | batch_69f4806d93dc8190b9dff4c63186faff |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 1:50 p.m.