Triple
T33060450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liski |
E845960
|
entity |
| Predicate | hasRailwayClassificationYard |
P190696
|
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: [Liski, hasRailwayClassificationYard, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRailwayClassificationYard Context triple: [Liski, hasRailwayClassificationYard, true]
-
A.
hasRailYard
Indicates that one entity possesses, contains, or includes a rail yard as part of its facilities or infrastructure.
-
B.
hasRailFacility
Indicates that an entity possesses or is served by a rail-related facility, such as a railway station, terminal, or yard.
-
C.
hasRailwayZone
Indicates that a location or railway entity falls under the jurisdiction or coverage area of a specific railway zone.
-
D.
railroadClass
Indicates the classification or category of a railroad according to an established system (e.g., by size, revenue, or regulatory status).
-
E.
hasRackRailway
Indicates that one entity possesses or includes a rack railway system connecting locations or operating within its area.
- 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_69f3495333b8819095e9af56855b9061 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fcce2cf9188190b3f65b362203a6a3 |
completed | May 7, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69fcccee6240819084680887731ff64b |
completed | May 7, 2026, 5:33 p.m. |
| PDg | Predicate description generation | batch_69fccdd2d84481909a7ce22407def9c7 |
completed | May 7, 2026, 5:37 p.m. |
Created at: May 1, 2026, 1:25 a.m.