Triple
T19927245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Didube |
E478956
|
entity |
| Predicate | hasMarshrutkaTerminal |
P137863
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Didube, hasMarshrutkaTerminal, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMarshrutkaTerminal Context triple: [Didube, hasMarshrutkaTerminal, true]
-
A.
hasPassengerTerminal
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
-
B.
hasPassengerTerminalFunction
Indicates that something serves the role or performs the function of a passenger terminal, supporting the handling and movement of passengers.
-
C.
hasCargoTerminal
Indicates that a location or facility includes or is equipped with a cargo terminal for handling freight.
-
D.
hasTramDestination
Indicates that a tram route or service goes to or terminates at a specified destination.
-
E.
hasMouthOfTransportRoute
Indicates that a transport route has a specific mouth or endpoint location where it begins, ends, or opens into another area or network.
- F. None of above. chosen
Provenance (4 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659ca52c881908dc8053bf61be4c4 |
completed | April 20, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69e537f070b481908958e0e5911dcdc1 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:53 p.m.