Triple
T29887533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Riggenbach rack system |
E759056
|
entity |
| Predicate | rackMounting |
P83207
|
FINISHED |
| Object | rack fixed to sleepers between running rails |
—
|
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: rack fixed to sleepers between running rails | Statement: [Riggenbach rack system, rackMounting, rack fixed to sleepers between running rails]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rackMounting Context triple: [Riggenbach rack system, rackMounting, rack fixed to sleepers between running rails]
-
A.
bellMounting
Indicates that one entity is mounted, fixed, or installed as a bell onto another supporting structure or surface.
-
B.
canBeRackMounted
chosen
Indicates that an entity is suitable or designed to be installed in a standard equipment rack.
-
C.
coolerMounting
Indicates that one object is mounted, attached, or fixed in place to serve as a cooler for another object.
-
D.
barrelMounting
Indicates that one object is mounted to or supported by a barrel-like structure as its primary attachment point.
-
E.
trainMounting
Indicates a relationship where an entity is boarding or getting onto a train.
- 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_69f2245de2f48190a481404896b56254 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f676fdaee481908b38890b2e8aaf4b |
completed | May 2, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:01 p.m.