Triple
T29213122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London–Paris rail route |
E740593
|
entity |
| Predicate | borderControlRegime |
P121973
|
FINISHED |
| Object | juxtaposed controls |
—
|
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: juxtaposed controls | Statement: [London–Paris rail route, borderControlRegime, juxtaposed controls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderControlRegime Context triple: [London–Paris rail route, borderControlRegime, juxtaposed controls]
-
A.
borderControlSide
Indicates that one entity is positioned on or associated with a particular side or segment of a border control area or checkpoint.
-
B.
borderControlMeasure
chosen
Indicates a policy or action implemented to regulate, monitor, or restrict the movement of people or goods across a border.
-
C.
borderControlDirection
Indicates the direction in which border control procedures are applied or enforced between two locations or jurisdictions.
-
D.
borderControls
Indicates that one entity enforces or administers border control measures over another entity or at a specific boundary.
-
E.
borderControlCoordinatedWith
Indicates that one entity coordinated its border control activities or policies with another entity.
- 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_69fd8e5f7c4c8190ab8e2f2a7bb1bd79 |
completed | May 8, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69fd8d8a16f08190b9e880901bfa44fe |
completed | May 8, 2026, 7:15 a.m. |
Created at: April 28, 2026, 12:12 p.m.