Triple
T24167080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Rail Mark 2 sleeping coaches |
E599017
|
entity |
| Predicate | hasBuffers |
P155567
|
FINISHED |
| Object | side buffers |
—
|
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: side buffers | Statement: [British Rail Mark 2 sleeping coaches, hasBuffers, side buffers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBuffers Context triple: [British Rail Mark 2 sleeping coaches, hasBuffers, side buffers]
-
A.
hasQueue
Indicates that an entity maintains or is associated with a queue, typically representing an ordered list of items or tasks awaiting processing.
-
B.
hasBinary
Indicates that one entity is associated with another entity in a binary (two-component) relationship, typically as one of the two members of a pair.
-
C.
hasPipes
Indicates that one entity is equipped with, contains, or is connected to one or more pipes.
-
D.
hasReceiver
Indicates that an entity serves as the recipient or target of something provided, sent, or directed by another entity.
-
E.
hasInput
Indicates that an entity receives or takes another entity as an input to its process, function, or operation.
- 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_69e288cbd62881909de32ca64a70c17b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27c9ddfcc819096697a844b300cce |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c42f942c8190b103ff29a60fef34 |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f27a753ca8819095706970d368f762 |
completed | April 29, 2026, 9:39 p.m. |
Created at: April 17, 2026, 11:33 p.m.