Triple
T1290401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Positive Train Control |
E27532
|
entity |
| Predicate | safetyDomain |
P12725
|
FINISHED |
| Object | railway signaling |
—
|
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: railway signaling | Statement: [Positive Train Control, safetyDomain, railway signaling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyDomain Context triple: [Positive Train Control, safetyDomain, railway signaling]
-
A.
regulatoryDomain
Indicates that one entity defines or governs the rules, policies, or constraints under which another entity must operate.
-
B.
safety
chosen
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.
sectorProtected
Indicates that a particular sector or area is safeguarded from harm, access, or exploitation by some form of protection or regulation.
-
D.
hasSecurityArea
Indicates that an entity is associated with, assigned to, or falls within a defined security-controlled area or zone.
-
E.
safetyRequirement
Indicates that one entity specifies or imposes conditions, standards, or measures necessary to ensure the safety of another entity or activity.
- 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0d6af908190ade9c481cc6f0ad8 |
completed | March 1, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69a4bee41ca08190b0ad6f7ea40c0b62 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.