Triple
T4073428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UPS Next Day Air |
E86701
|
entity |
| Predicate | hazmatSupport |
P53343
|
FINISHED |
| Object | accepts certain hazardous materials subject to regulations |
—
|
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: accepts certain hazardous materials subject to regulations | Statement: [UPS Next Day Air, hazmatSupport, accepts certain hazardous materials subject to regulations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hazmatSupport Context triple: [UPS Next Day Air, hazmatSupport, accepts certain hazardous materials subject to regulations]
-
A.
hazardType
Indicates the specific kind or category of hazard associated with an entity or situation.
-
B.
hasNotableHazard
Indicates that an entity is associated with a significant risk, danger, or harmful condition that is noteworthy or exceptional.
-
C.
hazardScope
Indicates the range or extent within which a particular hazard is relevant, applicable, or has effect.
-
D.
safetyEquipment
Indicates that one entity serves as safety equipment used to protect another entity from harm or danger.
-
E.
hasEmergencySystems
Indicates that the subject is equipped with or includes systems designed to detect, respond to, or manage emergency situations.
- F. None of above. chosen
Provenance (4 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_69aed93ebe448190a1f1686e28740ac9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc22be988190a2b6575d4f5e0f7b |
completed | March 9, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69aef9061d2481908307cafc9e9b32c0 |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefa5c52648190b001027f4dba75cb |
completed | March 9, 2026, 4:50 p.m. |
Created at: March 9, 2026, 3:39 p.m.