Triple
T7791086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AC-7 |
E180179
|
entity |
| Predicate | smokeManagementReason |
P76097
|
FINISHED |
| Object | cab-forward design to keep smoke away from crew in tunnels and snow sheds |
—
|
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: cab-forward design to keep smoke away from crew in tunnels and snow sheds | Statement: [AC-7, smokeManagementReason, cab-forward design to keep smoke away from crew in tunnels and snow sheds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: smokeManagementReason Context triple: [AC-7, smokeManagementReason, cab-forward design to keep smoke away from crew in tunnels and snow sheds]
-
A.
smokeManagementPurpose
chosen
Indicates that an action, plan, or measure is undertaken specifically to control, reduce, or otherwise manage smoke and its impacts.
-
B.
smokeUse
Indicates that an entity uses or consumes tobacco or other substances by smoking.
-
C.
canBeSmoked
Indicates that something is suitable or able to be consumed by smoking.
-
D.
usesTobaccoType
Indicates that an entity consumes or makes use of a specified type or form of tobacco.
-
E.
smokeSystem
Indicates that an entity is equipped with or associated with a smoke-generating system (e.g., for signaling, testing, or special effects).
- 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_69ca827d22208190b4dc5aa680edcf5d |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78a6d88819093f83528fe88b182 |
completed | March 30, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cae9111b2481909684a2d4aa4831c2 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:30 p.m.