Triple
T23553823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DB Class 481 |
E578124
|
entity |
| Predicate | formationDetail |
P33619
|
FINISHED |
| Object | two permanently coupled 2-car sets (481+482) |
—
|
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 permanently coupled 2-car sets (481+482) | Statement: [DB Class 481, formationDetail, two permanently coupled 2-car sets (481+482)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formationDetail Context triple: [DB Class 481, formationDetail, two permanently coupled 2-car sets (481+482)]
-
A.
layoutDetail
Indicates the specific arrangement or configuration details of how elements are laid out in relation to each other.
-
B.
compositionDetail
chosen
Indicates that one entity specifies or describes the internal makeup, structure, or constituent elements of another entity.
-
C.
formationType
Indicates the specific structural or organizational configuration in which something is arranged, created, or formed.
-
D.
outputDetail
Indicates that one entity specifies the level, amount, or granularity of information or results produced by another entity.
-
E.
scopeDetail
Indicates a more specific or refined characterization of the extent, boundaries, or coverage of something within a broader scope.
- 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_69e245fa93448190919cb04534560542 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1aed17fc881908b45dcde14790d42 |
completed | April 29, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69f118afabd88190bd88f49597d120e8 |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:11 p.m.