Triple
T28919284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krzyż Zasługi z Mieczami |
E733461
|
entity |
| Predicate | riskCondition |
P8576
|
FINISHED |
| Object | particular danger to life or health |
—
|
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: particular danger to life or health | Statement: [Krzyż Zasługi z Mieczami, riskCondition, particular danger to life or health]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riskCondition Context triple: [Krzyż Zasługi z Mieczami, riskCondition, particular danger to life or health]
-
A.
riskElement
Indicates that one entity is a risk-related component, factor, or contributor associated with another entity within a risk context.
-
B.
riskType
Indicates the category or nature of risk associated with an entity, event, or relationship.
-
C.
riskFeature
chosen
Indicates that one entity possesses or exhibits a characteristic, condition, or attribute that increases the likelihood or severity of a negative outcome for another entity or situation.
-
D.
riskDescription
Indicates a textual explanation of the nature, causes, and potential impact of a specific risk.
-
E.
riskTaken
Indicates that an entity has undertaken an action or decision involving exposure to potential loss, harm, or uncertainty.
- 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_69f05b0a5cc0819094828367ae204b70 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65b18c1208190add0150dd5e95270 |
completed | May 2, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f6576487e081908d802f1caf59c423 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 8:18 a.m.