Triple
T4058197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osu Kannon Temple |
E84744
|
entity |
| Predicate | relocationCentury |
P53056
|
FINISHED |
| Object | 17th century |
—
|
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: 17th century | Statement: [Osu Kannon Temple, relocationCentury, 17th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relocationCentury Context triple: [Osu Kannon Temple, relocationCentury, 17th century]
-
A.
reorganizedInCentury
Indicates that an entity underwent a significant reorganization or structural change during the specified century.
-
B.
relocationYear
Indicates the year in which an entity was moved or transferred from one location to another.
-
C.
originalCentury
Indicates the century in which something was originally created, produced, or came into existence.
-
D.
century
Indicates that an entity is associated with, occurs in, or belongs to a particular 100-year time period.
-
E.
wasRepopulatedInCentury
Indicates that a place or region, previously depopulated or abandoned, became populated again during the specified century.
- 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_69aed933bec881909edfa28ebb69c634 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefbaefcb081908aab3963dcd61a20 |
completed | March 9, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69aef90249e4819095e9e043bc4aa9a6 |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aef9fcb31c819098d5287b6fc84f4e |
completed | March 9, 2026, 4:49 p.m. |
Created at: March 9, 2026, 3:38 p.m.