Triple
T20544123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Load and Resistance Factor Design |
E504419
|
entity |
| Predicate | safetyFormat |
P140490
|
FINISHED |
| Object | partial safety factor method |
—
|
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: partial safety factor method | Statement: [Load and Resistance Factor Design, safetyFormat, partial safety factor method]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyFormat Context triple: [Load and Resistance Factor Design, safetyFormat, partial safety factor method]
-
A.
safetyContext
Indicates the circumstances, conditions, or environment that affect how safe an action, object, or situation is.
-
B.
safetyFunction
Indicates that one entity serves as a safety-related function or mechanism that protects, safeguards, or reduces risk for another entity or process.
-
C.
safety
Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
-
D.
safetyProfile
Indicates the overall level and characteristics of risk or harm associated with something, typically summarizing how safe it is under specified conditions.
-
E.
safetyResponse
Indicates how an entity reacts or what measures it takes in response to a potential or actual safety-related situation.
- 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_69e0b4b476648190bc6019622ae54d3c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a2957c308190aab81127f82f8aa6 |
completed | April 20, 2026, 10:03 p.m. |
| PD | Predicate disambiguation | batch_69e59fe5592c8190bb6122b784496d02 |
completed | April 20, 2026, 3:39 a.m. |
| PDg | Predicate description generation | batch_69e5a6a824748190bbe6192d73f3c613 |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:38 a.m.