Triple
T34542556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matsue Castle |
E886839
|
entity |
| Predicate | hasMainKeepHeight |
P9788
|
FINISHED |
| Object | approximately 30 meters |
—
|
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: approximately 30 meters | Statement: [Matsue Castle, hasMainKeepHeight, approximately 30 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainKeepHeight Context triple: [Matsue Castle, hasMainKeepHeight, approximately 30 meters]
-
A.
hasMainKeepType
Indicates the specific type or category of main keep associated with a structure or site.
-
B.
hasHeight
chosen
Indicates that one entity possesses a specific vertical measurement or stature.
-
C.
hasSignificantHeight
Indicates that one entity’s height is notably large or substantial relative to a given standard or to other entities.
-
D.
hasMainSpanLength
Indicates the relationship specifying the primary or main span’s length associated with an entity.
-
E.
hasMainStructure
Indicates that one entity serves as the primary or central structural component 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_69f349ce5eb881909e431c670944aa68 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a01b241f7308190bedb7522cb5dc069 |
completed | May 11, 2026, 10:41 a.m. |
| PD | Predicate disambiguation | batch_6a01b19ff12c81908ee1b188b4a3e118 |
completed | May 11, 2026, 10:38 a.m. |
Created at: May 1, 2026, 2:02 a.m.