Triple
T4904167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tbilisi Metro |
E109873
|
entity |
| Predicate | rollingStockOrigin |
P55577
|
FINISHED |
| Object | Soviet-built trains |
—
|
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: Soviet-built trains | Statement: [Tbilisi Metro, rollingStockOrigin, Soviet-built trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rollingStockOrigin Context triple: [Tbilisi Metro, rollingStockOrigin, Soviet-built trains]
-
A.
hasRollingStockOrigin
chosen
Indicates that a piece of rolling stock originates from, or was initially based in, a particular location or source.
-
B.
rollingStockManufacturer
Indicates that one entity is the company or organization that manufactures the rolling stock (rail vehicles) used or owned by another entity.
-
C.
rollingStockType
Indicates the specific category or type of railway rolling stock associated with an entity (e.g., locomotive, passenger car, freight wagon).
-
D.
rollingStockSupplier
Indicates that one entity supplies or provides rolling stock (such as railway vehicles) to another entity.
-
E.
rollingStockFamily
Indicates a relationship where a piece of rolling stock belongs to, or is classified under, a particular family or series of related rolling stock designs.
- 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_69bd441180708190ba42ffb44fea533a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd706245e48190a61d573438461c30 |
completed | March 20, 2026, 4:05 p.m. |
| PD | Predicate disambiguation | batch_69bd6c306b188190a08a7856beb76db4 |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:29 p.m.