Triple
T21258103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gyeongbokgung |
E523920
|
entity |
| Predicate | partiallyDemolishedDuring |
P114779
|
FINISHED |
| Object | Japanese colonial period |
—
|
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: Japanese colonial period | Statement: [Gyeongbokgung, partiallyDemolishedDuring, Japanese colonial period]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partiallyDemolishedDuring Context triple: [Gyeongbokgung, partiallyDemolishedDuring, Japanese colonial period]
-
A.
partiallyDemolishedInCentury
Indicates that an entity was only partly demolished during a specified century, rather than being completely destroyed.
-
B.
partiallyDestroyed
Indicates that an entity has been damaged or ruined to a significant extent but not completely destroyed.
-
C.
demolishedAsPartOf
Indicates that one entity was demolished as a component or consequence of a larger demolition event or project involving another entity.
-
D.
demolishedPortions
chosen
Indicates that certain parts or sections of an object, structure, or entity have been destroyed or torn down.
-
E.
hasDemolitionOrDestruction
Indicates that one entity causes, undergoes, or is associated with the demolition or destruction 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_69e0b5146c108190adc9adb73e90abff |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e735e477d08190be17ad5384d69a80 |
completed | April 21, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69e5f61239708190ab7b3c83ae848a0d |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:58 p.m.