Triple
T26848710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cab Forward |
E675994
|
entity |
| Predicate | hasSafetyBenefit |
P60758
|
FINISHED |
| Object | reduces crew exposure to smoke and exhaust gases |
—
|
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: reduces crew exposure to smoke and exhaust gases | Statement: [Cab Forward, hasSafetyBenefit, reduces crew exposure to smoke and exhaust gases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSafetyBenefit Context triple: [Cab Forward, hasSafetyBenefit, reduces crew exposure to smoke and exhaust gases]
-
A.
safetyBenefit
chosen
Indicates that one entity provides, contributes to, or results in an improvement in the safety or risk reduction experienced by another entity.
-
B.
hasSafetyCharacteristic
Indicates that an entity possesses a specific safety-related property, feature, or attribute.
-
C.
hasBenefit
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
D.
hasSafetyInformation
Indicates that one entity provides or is associated with safety-related details, warnings, or guidelines about another entity.
-
E.
safetyLegacy
Indicates that an entity’s current safety status, practices, or conditions are influenced or determined by past safety decisions, standards, or incidents.
- 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_69eee9b8d5e88190a07d3455c0fbb21f |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f6691f5e188190b12c7b2eb729a45e |
completed | May 2, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69f66598d6008190a7ca8ff80399fd34 |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 27, 2026, 5:14 a.m.