Triple
T21831171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Rail Class 90 |
E538996
|
entity |
| Predicate | hasMultipleWorkingSystem |
P97109
|
FINISHED |
| Object | Time-division multiplex (TDM) |
—
|
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: Time-division multiplex (TDM) | Statement: [British Rail Class 90, hasMultipleWorkingSystem, Time-division multiplex (TDM)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMultipleWorkingSystem Context triple: [British Rail Class 90, hasMultipleWorkingSystem, Time-division multiplex (TDM)]
-
A.
multipleWorkingSystem
chosen
Indicates that an entity is associated with or operates within more than one working system simultaneously.
-
B.
hasMultipleWorking
Indicates that an entity is associated with more than one working instance, role, or configuration simultaneously.
-
C.
supportsMultipleWindows
Indicates that the subject can handle or display more than one window or view simultaneously.
-
D.
isMultiplatform
Indicates that something is designed to operate or be available across multiple platforms or environments.
-
E.
supportsMultipleTerminals
Indicates that an entity is capable of handling or operating with more than one terminal or endpoint simultaneously.
- 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_69e0c475cda88190987d08f23caebdc1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f091362d9081909f00ad7a2806d5cb |
completed | April 28, 2026, 10:51 a.m. |
| PD | Predicate disambiguation | batch_69e6be8c14748190bdcc44a14d50bea4 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:55 p.m.