Triple
T24281108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Treasure of South Korea |
E605541
|
entity |
| Predicate | numberingSystemType |
P3378
|
FINISHED |
| Object | sequential designation number |
—
|
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: sequential designation number | Statement: [National Treasure of South Korea, numberingSystemType, sequential designation number]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberingSystemType Context triple: [National Treasure of South Korea, numberingSystemType, sequential designation number]
-
A.
numberingSystemBasedOn
Indicates that one numbering system is derived from, structured according to, or conceptually dependent on another numbering system.
-
B.
laterNumberingSystem
Indicates that one numbering system was adopted or used after another, reflecting a subsequent or more recent scheme of numbering.
-
C.
hasNumberSystem
Indicates that an entity possesses or uses a particular system for representing and organizing numbers.
-
D.
followsCountingSystemOf
Indicates that one entity uses or adheres to the same counting or numeral system as another entity.
-
E.
numberingType
chosen
Indicates the scheme or style used to assign sequential numbers or labels within an ordered set.
- 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_69e295480d0c8190846fc3c2e2da1d4c |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28f5227888190b1713af150fa30a1 |
completed | April 29, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69f1c457a2908190993824395b3c365d |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:08 a.m.