Triple
T212351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | List of World Heritage in Danger |
E4745
|
entity |
| Predicate | dangerType |
P1950
|
FINISHED |
| Object | armed conflict |
—
|
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: armed conflict | Statement: [List of World Heritage in Danger, dangerType, armed conflict]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dangerType Context triple: [List of World Heritage in Danger, dangerType, armed conflict]
-
A.
hazardType
chosen
Indicates the specific kind or category of hazard associated with an entity or situation.
-
B.
threat
Indicates a relationship where one entity expresses or poses potential harm, danger, or negative consequences toward another entity.
-
C.
threatenedBy
Indicates that one entity poses a danger or potential harm to another entity.
-
D.
attackType
Indicates the specific method, style, or category of attack used in an aggressive or hostile action between entities.
-
E.
riskLevel
Indicates the degree of potential harm, loss, or adverse outcome associated with a particular situation, action, or 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c313d108190a65d3e939f961bef |
completed | Feb. 28, 2026, 3:08 a.m. |
| PD | Predicate disambiguation | batch_69a25b509400819093a6c1a1bac861e3 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:52 a.m.