Triple
T13347992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chubu tourism area |
E318005
|
entity |
| Predicate | includesLandscape |
P22129
|
FINISHED |
| Object | coastal plains |
—
|
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: coastal plains | Statement: [Chubu tourism area, includesLandscape, coastal plains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesLandscape Context triple: [Chubu tourism area, includesLandscape, coastal plains]
-
A.
hasLandscapeType
Indicates that an entity possesses or is characterized by a particular type or category of landscape.
-
B.
supportsLandscapeMode
Indicates that an entity is capable of functioning or being displayed correctly when oriented in landscape mode.
-
C.
hasLandscapeFeatures
chosen
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
-
D.
hasPortrait
Indicates that one entity possesses, displays, or is associated with a portrait depicting another entity.
-
E.
includesFiguresFrom
Indicates that one entity contains or incorporates figures that originate from or are part of another entity.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e8b28e48190a23194e03a74b41b |
completed | April 11, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69d98f6e53d88190bd6aa42f69b10ffb |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:31 p.m.