Triple
T8254029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milan series 1500 Peter Witt trams |
E193025
|
entity |
| Predicate | bogies |
P44072
|
FINISHED |
| Object | two-bogie design |
—
|
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: two-bogie design | Statement: [Milan series 1500 Peter Witt trams, bogies, two-bogie design]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bogies Context triple: [Milan series 1500 Peter Witt trams, bogies, two-bogie design]
-
A.
bogieType
chosen
Indicates the specific configuration or classification of a vehicle’s bogie (wheel assembly) used in its design or operation.
-
B.
bore
Indicates that one entity caused another entity to feel uninterested, tired, or lacking in engagement.
-
C.
railwayCarriageUsedFor
Indicates that a railway carriage is employed or designated for a particular purpose, function, or type of use.
-
D.
formerRollingStock
Indicates that an entity was previously used as rolling stock (e.g., railway vehicles) but no longer serves in that capacity.
-
E.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
- 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_69ca82dfad9c8190b8cd18fb89f50f40 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78f8eccc8190b43204bf2f8defc1 |
completed | March 31, 2026, 7:34 a.m. |
| PD | Predicate disambiguation | batch_69cb36b6d5548190b665a6cce14c69f7 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:48 p.m.