Triple
T23196046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Rail second-generation DMUs |
E579870
|
entity |
| Predicate | used on |
P2367
|
FINISHED |
| Object | non-electrified lines in Great Britain |
—
|
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: non-electrified lines in Great Britain | Statement: [British Rail second-generation DMUs, used on, non-electrified lines in Great Britain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: used on Context triple: [British Rail second-generation DMUs, used on, non-electrified lines in Great Britain]
-
A.
usedOn
chosen
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
-
B.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
C.
usedVia
Indicates that an entity performs or achieves something by means of, or through the use of, another entity or mechanism.
-
D.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
E.
usedDuring
Indicates that one entity is employed, applied, or active in the course of another entity’s process, event, or time period.
- 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_69e24600eed08190bd7e5295653a1503 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18fdb279c81908dcc46f2786a86cd |
completed | April 29, 2026, 4:58 a.m. |
| PD | Predicate disambiguation | batch_69ef8a041c0081909afb670d17a5aaba |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4:06 p.m.