Triple
T20205848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Union Pacific Big Boy class locomotives |
E493346
|
entity |
| Predicate | totalLocomotiveAndTenderWeight |
P96098
|
FINISHED |
| Object | over 1,200,000 lb |
—
|
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: over 1,200,000 lb | Statement: [Union Pacific Big Boy class locomotives, totalLocomotiveAndTenderWeight, over 1,200,000 lb]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalLocomotiveAndTenderWeight Context triple: [Union Pacific Big Boy class locomotives, totalLocomotiveAndTenderWeight, over 1,200,000 lb]
-
A.
locomotiveWeight
chosen
Indicates the weight or mass of a locomotive in the relationship.
-
B.
totalEngineWeight
Indicates the combined weight of all engines associated with a given object or system.
-
C.
typeOfLocomotivesProduced
Indicates the specific kinds or categories of locomotives that are manufactured or produced by an entity.
-
D.
locomotiveConfiguration
Indicates the specific arrangement and type of power and running units (e.g., wheel or axle layout) that define how a locomotive is configured.
-
E.
typicalLocomotiveClass
Indicates that one locomotive class is the standard or most commonly used class for a given context, operator, or service.
- 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_69da6269614c8190bb40475d9d477358 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66d922ebc8190ae012da8ceba74dd |
completed | April 20, 2026, 6:16 p.m. |
| PD | Predicate disambiguation | batch_69e55b14c9d8819095453d0504d9222f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:38 p.m.