Triple
T5961338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eurasia Tunnel |
E132643
|
entity |
| Predicate | hasTrafficMonitoringSystem |
P49308
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Eurasia Tunnel, hasTrafficMonitoringSystem, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrafficMonitoringSystem Context triple: [Eurasia Tunnel, hasTrafficMonitoringSystem, yes]
-
A.
hasTrafficControl
Indicates that some form of traffic management or regulation mechanism is present or applied to a given route, intersection, or transportation element.
-
B.
hasTrafficRegime
Indicates that a specified traffic control or regulatory system applies to a given road, area, or transport context.
-
C.
hasTrafficControlCenter
chosen
Indicates that an entity possesses or is served by a traffic control center responsible for monitoring and managing traffic operations.
-
D.
hasTrafficSignals
Indicates that traffic control signals are present at or associated with a given location or roadway feature.
-
E.
hasTrafficPattern
Indicates that there is a characteristic or recurring flow of traffic associated with an entity, such as its typical volume, direction, or timing of movement.
- 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_69c0086c2364819091e9fe2f58fa2517 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03fb7f8a88190a8bd45208bda4a03 |
completed | March 22, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69c0335a635881909c58c1ef0f97f1e8 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4:02 p.m.