Triple
T5592294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kang Pan-sok Revolutionary Museum |
E146906
|
entity |
| Predicate | usesNarrative |
P11859
|
FINISHED |
| Object | revolutionary martyrdom |
—
|
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: revolutionary martyrdom | Statement: [Kang Pan-sok Revolutionary Museum, usesNarrative, revolutionary martyrdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesNarrative Context triple: [Kang Pan-sok Revolutionary Museum, usesNarrative, revolutionary martyrdom]
-
A.
usesNarrativeStyle
Indicates that one entity employs or adopts a particular narrative style in presenting or structuring content or information.
-
B.
hasNarrative
chosen
Indicates that one entity contains, presents, or is associated with a story or narrative about another entity or subject.
-
C.
containsNarrativeOf
Indicates that one entity includes or presents the story, account, or narrative content of another entity.
-
D.
narrative
Indicates that one entity tells, presents, or conveys a story or sequence of events about another entity or situation.
-
E.
hasNarrativeRole
Indicates that an entity participates in a narrative with a specific functional role (e.g., protagonist, antagonist, narrator) relative to the story.
- 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_69c009036c408190981a8d690b679b67 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020a3365c8190bd223226c0a6969f |
completed | March 22, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69c01b16b9bc8190ab0b945507d90e05 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:38 p.m.