Triple
T13800148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kållerado |
E331616
|
entity |
| Predicate | safetyRestraints |
P26738
|
FINISHED |
| Object | grab rails |
—
|
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: grab rails | Statement: [Kållerado, safetyRestraints, grab rails]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyRestraints Context triple: [Kållerado, safetyRestraints, grab rails]
-
A.
restraintType
Indicates the specific kind or method of restraint applied in a given situation or relationship.
-
B.
hasBeenSafeSeatFor
Indicates that a political position or constituency has consistently been held securely by a particular party or candidate, with little risk of losing it in elections.
-
C.
safetyCategory
Indicates the classification of something according to its level or type of safety.
-
D.
safetyEquipment
chosen
Indicates that one entity serves as safety equipment used to protect another entity from harm or danger.
-
E.
safetyConcept
Indicates that something embodies, represents, or is associated with a principle, idea, or framework related to safety.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de025ce9148190b23370f6a522ff7a |
completed | April 14, 2026, 9:01 a.m. |
| PD | Predicate disambiguation | batch_69dbc85fb600819098a2aab48169be96 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:11 p.m.