Triple
T5062227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gyeonghuigung |
E114047
|
entity |
| Predicate | partiallyDemolishedFor |
P17180
|
FINISHED |
| Object | modern urban development |
—
|
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: modern urban development | Statement: [Gyeonghuigung, partiallyDemolishedFor, modern urban development]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partiallyDemolishedFor Context triple: [Gyeonghuigung, partiallyDemolishedFor, modern urban development]
-
A.
partiallyDestroyed
Indicates that an entity has been damaged or ruined to a significant extent but not completely destroyed.
-
B.
partlyDismantledBy
chosen
Indicates that an entity has been only partially taken apart, removed, or deconstructed by another agent or process.
-
C.
partiallyDemolishedInCentury
Indicates that an entity was only partly demolished during a specified century, rather than being completely destroyed.
-
D.
hasDemolitionOrDestruction
Indicates that one entity causes, undergoes, or is associated with the demolition or destruction of another entity.
-
E.
demolishedWith
Indicates that one entity was destroyed or torn down using another specified tool, method, or agent.
- 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_69bd443c0c8c81908663b77afb28e165 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7475be3c819085cde8ec544c407e |
completed | March 20, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69bd715622b48190a3e8e49a5ef62b4a |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:38 p.m.