Triple
T106487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Union Pacific Railroad |
E2147
|
entity |
| Predicate | BaileyYardFunction |
P4905
|
FINISHED |
| Object | world’s largest railroad classification yard |
—
|
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: world’s largest railroad classification yard | Statement: [Union Pacific Railroad, BaileyYardFunction, world’s largest railroad classification yard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: BaileyYardFunction Context triple: [Union Pacific Railroad, BaileyYardFunction, world’s largest railroad classification yard]
-
A.
isOutdoorFacility
Indicates that a facility is located outdoors or primarily functions in an open-air environment.
-
B.
usesBuilding
Indicates that one entity makes use of, occupies, or operates within a particular building.
-
C.
hasSidewalk
Indicates that a location, path, or roadway is accompanied by a designated sidewalk area for pedestrian use.
-
D.
buildingType
Indicates the specific category or function that characterizes what kind of building something is.
-
E.
lays
Indicates that one entity deposits or places something, typically eggs or objects, onto a surface or in a location.
- 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a256ec650c8190bee2067e37065527 |
completed | Feb. 28, 2026, 2:46 a.m. |
| PD | Predicate disambiguation | batch_69a2563d33788190999d471b486d5603 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a256ea776081908fec36c3fdfb8d84 |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.