Triple
T23751866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renfe 447 series |
E586990
|
entity |
| Predicate | controlCab |
P21781
|
FINISHED |
| Object | driving cab at both ends |
—
|
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: driving cab at both ends | Statement: [Renfe 447 series, controlCab, driving cab at both ends]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: controlCab Context triple: [Renfe 447 series, controlCab, driving cab at both ends]
-
A.
operatorCab
Indicates that a person or organization serves as the operating company or carrier responsible for running a specific cab or taxi service.
-
B.
hasControlCab
chosen
Indicates that an entity is equipped with or includes a control cab used for operating or controlling it.
-
C.
controlRoomFeature
Indicates that a feature, element, or characteristic is part of, present in, or associated with a control room.
-
D.
controlsSystem
Indicates that one entity has the authority or capability to direct, manage, or regulate the operation of a system.
-
E.
controlStand
Indicates that one entity manages, directs, or regulates the operation or behavior of another entity or system.
- 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_69e2490a0eec81908cdef8a862828d7a |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bcc289e08190a8036bb16dd0220a |
completed | April 29, 2026, 8:09 a.m. |
| PD | Predicate disambiguation | batch_69f155f012808190a4b1cbc155558ade |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 7:13 p.m.