Triple
T71122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donner Pass |
E1422
|
entity |
| Predicate | railroadEngineeringFeature |
P3554
|
FINISHED |
| Object | snow sheds |
—
|
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: snow sheds | Statement: [Donner Pass, railroadEngineeringFeature, snow sheds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railroadEngineeringFeature Context triple: [Donner Pass, railroadEngineeringFeature, snow sheds]
-
A.
railwayLine
Indicates that there is a railway line connection or route associated with or passing through the referenced entity.
-
B.
hasRailSystem
Indicates that an entity possesses or is served by a rail-based transportation system.
-
C.
servedByRailroad
Indicates that a location or facility is provided with transportation or service by a railroad line or company.
-
D.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
E.
rollingStockType
Indicates the specific category or type of railway rolling stock associated with an entity (e.g., locomotive, passenger car, freight wagon).
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24f6997c081908b202f937eb2b14f |
completed | Feb. 28, 2026, 2:14 a.m. |
| PD | Predicate disambiguation | batch_69a24eab7f408190a8275cb82474f575 |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a24f65170c8190bc541c8351456a4d |
completed | Feb. 28, 2026, 2:13 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.