Triple
T34542564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matsue Castle |
E886839
|
entity |
| Predicate | hasOriginalTenshu |
P197535
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Matsue Castle, hasOriginalTenshu, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalTenshu Context triple: [Matsue Castle, hasOriginalTenshu, yes]
-
A.
hasOriginalCharacter
Indicates that an entity includes, features, or is associated with an original character distinct from pre-existing or canonical characters.
-
B.
hasOriginalMecha
Indicates that an entity is associated with its initial or primary mecha design, model, or unit from which others may derive or be based.
-
C.
hasOriginalBuildings
Indicates that an entity possesses or still retains its initial or historically first-constructed buildings.
-
D.
hasOriginalVersion
Indicates that one entity is the original or initial version from which another entity is derived or adapted.
-
E.
originallyHad
Indicates that an entity previously possessed, contained, or was associated with something before a change, loss, or transformation occurred.
- F. None of above. chosen
Provenance (4 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_69fe991bca608190b524e419642f4243 |
completed | May 9, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69fe979fc1c4819091fc48d63ea12063 |
completed | May 9, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69fe991abc6c81908edbb98d61c9ca73 |
completed | May 9, 2026, 2:16 a.m. |
Created at: May 1, 2026, 2:02 a.m.