Triple
T29213131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London–Paris rail route |
E740593
|
entity |
| Predicate | safetySystemUsed |
P63490
|
FINISHED |
| Object | TVM cab signalling (on high-speed sections) |
—
|
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: TVM cab signalling (on high-speed sections) | Statement: [London–Paris rail route, safetySystemUsed, TVM cab signalling (on high-speed sections)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetySystemUsed Context triple: [London–Paris rail route, safetySystemUsed, TVM cab signalling (on high-speed sections)]
-
A.
hasIntruderDetectionSystem
Indicates that an entity is equipped with a system designed to detect unauthorized or intruding entities.
-
B.
safetySystemPlanned
Indicates that a safety system has been planned or scheduled for implementation in relation to the relevant entities.
-
C.
hasSafetyCharacteristic
chosen
Indicates that an entity possesses a specific safety-related property, feature, or attribute.
-
D.
measuresSafetyUsing
Indicates that an entity evaluates or assesses safety by employing a specified method, tool, or standard.
-
E.
hasEmergencySystems
Indicates that the subject is equipped with or includes systems designed to detect, respond to, or manage emergency situations.
- 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_69f07cba2f808190a2746477d4e8345b |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f6978fe97081908fe568091ad9b159 |
completed | May 3, 2026, 12:32 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 28, 2026, 12:12 p.m.