Triple
T7847699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | War Hazards Compensation Act |
E181962
|
entity |
| Predicate | typeOfHazardCovered |
P1950
|
FINISHED |
| Object | war |
—
|
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: war | Statement: [War Hazards Compensation Act, typeOfHazardCovered, war]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfHazardCovered Context triple: [War Hazards Compensation Act, typeOfHazardCovered, war]
-
A.
hazardType
chosen
Indicates the specific kind or category of hazard associated with an entity or situation.
-
B.
hazardScope
Indicates the range or extent within which a particular hazard is relevant, applicable, or has effect.
-
C.
hasNotableHazard
Indicates that an entity is associated with a significant risk, danger, or harmful condition that is noteworthy or exceptional.
-
D.
typeOfDiscriminationCovered
Indicates that a particular kind or category of discriminatory behavior is included within the scope of protections, rules, or analysis.
-
E.
emergencyTypesCovered
Indicates that certain kinds of emergencies are included within the scope of coverage, protection, or response defined by the relationship.
- 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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb164105fc8190a60aaa27dd619d5a |
completed | March 31, 2026, 12:33 a.m. |
| PD | Predicate disambiguation | batch_69cae92180f88190ae3d44c3de7adc93 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:49 p.m.