Triple
T21571649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liu Yongfu |
E532296
|
entity |
| Predicate | typeOfWarfareUsed |
P709
|
FINISHED |
| Object | asymmetric warfare |
—
|
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: asymmetric warfare | Statement: [Liu Yongfu, typeOfWarfareUsed, asymmetric warfare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfWarfareUsed Context triple: [Liu Yongfu, typeOfWarfareUsed, asymmetric warfare]
-
A.
usedWarfareType
chosen
Indicates the specific type or method of warfare that an entity employed in a conflict or military context.
-
B.
eraOfPrimaryMilitaryUse
Indicates the historical time period during which the subject was primarily used for military purposes.
-
C.
warfareType
Indicates the specific kind or category of warfare that characterizes a given conflict or military engagement.
-
D.
warfareCapability
Indicates the ability or capacity of an entity to engage in, conduct, or support acts of warfare.
-
E.
weaponsUsed
Indicates that one entity employed or utilized another entity as a weapon in carrying out an action or event.
- 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_69e0c460db088190828c64206a450273 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eee9cd50188190b44eb25fb87312bb |
completed | April 27, 2026, 4:45 a.m. |
| PD | Predicate disambiguation | batch_69e6320c8c2c81908bf031447d66a052 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:30 p.m.