Triple
T936293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M7 electric multiple unit |
E20201
|
entity |
| Predicate | hasControlCab |
P21781
|
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: [M7 electric multiple unit, hasControlCab, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasControlCab Context triple: [M7 electric multiple unit, hasControlCab, yes]
-
A.
hasControlTower
Indicates that one entity possesses, hosts, or is equipped with a control tower that manages or oversees its operations.
-
B.
hasCabinet
Indicates that one entity possesses, includes, or is equipped with a cabinet associated with it.
-
C.
hasChangeControl
Indicates that an entity is subject to a defined process for reviewing, approving, and managing modifications or updates.
-
D.
operatorCab
Indicates that a person or organization serves as the operating company or carrier responsible for running a specific cab or taxi service.
-
E.
hasEntranceControl
Indicates that an entity implements or is subject to mechanisms that regulate or control access to its entrance.
- 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_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b36558588190a2a9c710073624d1 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b29b245c8190b143f28b77fede3c |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b326d9d88190913c1a892a795707 |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:40 p.m.