Triple
T5839462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gorges du Fier |
E129554
|
entity |
| Predicate | safetyInfrastructure |
P34538
|
FINISHED |
| Object | guardrails |
—
|
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: guardrails | Statement: [Gorges du Fier, safetyInfrastructure, guardrails]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyInfrastructure Context triple: [Gorges du Fier, safetyInfrastructure, guardrails]
-
A.
hasSafetyInfrastructure
chosen
Indicates that appropriate safety-related structures, systems, or measures are present for the referenced entity or environment.
-
B.
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.
-
C.
safetyCategory
Indicates the classification of something according to its level or type of safety.
-
D.
significantInfrastructure
Indicates that an entity constitutes an important or critical piece of infrastructure within a system, network, or region.
-
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_69c0084af79c81908af128ccc29983d0 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c0334412388190bc594794ec5754f9 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:54 p.m.