Triple
T5453374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Rail Class 180 |
E122420
|
entity |
| Predicate | hasMultipleWorking |
P64406
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [British Rail Class 180, hasMultipleWorking, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMultipleWorking Context triple: [British Rail Class 180, hasMultipleWorking, yes]
-
A.
hasMultiple
Indicates that an entity is associated with more than one instance or occurrence of another related entity.
-
B.
hasWorkingMode
Indicates that an entity operates under or supports a particular mode or configuration of functioning.
-
C.
canOperateInMultiple
Indicates that an entity is capable of functioning or being used across more than one context, environment, or mode.
-
D.
hasConnectionToWork
Indicates that one entity is linked or related to another through a work-related or professional connection.
-
E.
hasWorkCount
Indicates the number of works (such as items, creations, or outputs) associated with a given entity.
- F. None of above. chosen
Provenance (4 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_69bd46424248819085282ddf50a565f3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd95be329c81908783420cf81b6af5 |
completed | March 20, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69bd919e8d18819098c4af6a015e5cc2 |
completed | March 20, 2026, 6:27 p.m. |
| PDg | Predicate description generation | batch_69bd95bd53f48190a03144beb290f2cb |
completed | March 20, 2026, 6:45 p.m. |
Created at: March 20, 2026, 2:08 p.m.