Triple
T34542558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matsue Castle |
E886839
|
entity |
| Predicate | hasNumberOfMainKeepInternalLevels |
P7355
|
FINISHED |
| Object | 6 internal levels |
—
|
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: 6 internal levels | Statement: [Matsue Castle, hasNumberOfMainKeepInternalLevels, 6 internal levels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfMainKeepInternalLevels Context triple: [Matsue Castle, hasNumberOfMainKeepInternalLevels, 6 internal levels]
-
A.
hasNumberOfLevels
chosen
Indicates that an entity possesses a specified count of distinct levels or tiers.
-
B.
hasMainKeepType
Indicates the specific type or category of main keep associated with a structure or site.
-
C.
hasLevelNumber
Indicates that an entity is associated with a specific level identified by a numerical value.
-
D.
numberOfLevels
Indicates the total count of hierarchical layers, stages, or floors associated with an entity.
-
E.
hasMultipleLevels
Indicates that something is organized into more than one hierarchical or structural level.
- 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_69feb342994081909481ec8ec5d44928 |
completed | May 9, 2026, 4:08 a.m. |
| PD | Predicate disambiguation | batch_69feb046e4e48190b96649aa28529cc9 |
completed | May 9, 2026, 3:55 a.m. |
Created at: May 1, 2026, 2:02 a.m.