Triple
T29467829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moscow railway stations |
E747426
|
entity |
| Predicate | hasInternationalCustomsControl |
P77375
|
FINISHED |
| Object | some stations |
—
|
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: some stations | Statement: [Moscow railway stations, hasInternationalCustomsControl, some stations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInternationalCustomsControl Context triple: [Moscow railway stations, hasInternationalCustomsControl, some stations]
-
A.
hasNoCustomsControl
Indicates that there is no customs inspection or control applied between the related entities.
-
B.
hasCustomsReportingRequirement
Indicates that an entity is obligated to report certain activities, goods, or transactions to customs authorities in accordance with applicable regulations.
-
C.
hasSpecialCustomsStatus
Indicates that an entity holds a designated special customs status affecting how it is treated in customs procedures.
-
D.
hadCustoms
Indicates that one entity possessed or maintained particular customs, traditions, or habitual practices associated with another entity or context.
-
E.
hasCustomsCheckpoint
chosen
Indicates that a location or route includes an official customs inspection point where goods, vehicles, or people are checked for compliance with border regulations.
- 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_69f0bd42cf308190bb01b20bc5b7c2d0 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69fe8f74748c8190bd14a856c057f9f7 |
completed | May 9, 2026, 1:35 a.m. |
| PD | Predicate disambiguation | batch_69fe8e7ed8088190929e0df67aca4de9 |
completed | May 9, 2026, 1:31 a.m. |
Created at: April 28, 2026, 3:54 p.m.