Triple
T5225082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FEMA Region VIII |
E117964
|
entity |
| Predicate | focusesOnHazards |
P1950
|
FINISHED |
| Object | floods |
—
|
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: floods | Statement: [FEMA Region VIII, focusesOnHazards, floods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusesOnHazards Context triple: [FEMA Region VIII, focusesOnHazards, floods]
-
A.
hasNotableHazard
Indicates that an entity is associated with a significant risk, danger, or harmful condition that is noteworthy or exceptional.
-
B.
hazardScope
Indicates the range or extent within which a particular hazard is relevant, applicable, or has effect.
-
C.
hasNavigationHazardRelevance
Indicates that something is relevant to, affected by, or poses a potential hazard to navigation.
-
D.
hazardType
chosen
Indicates the specific kind or category of hazard associated with an entity or situation.
-
E.
safetyRelevant
Indicates that the associated entity, condition, or information has a direct impact on safety or is critical for preventing harm or accidents.
- 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_69bd4465e03081909bfcfd7113062590 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7adb034c819086bf8a85fbf158f4 |
completed | March 20, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69bd77bd2a448190a9ae5afd2585a7b9 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:48 p.m.