Triple
T29697655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Savupirtti smoke cottage |
E751394
|
entity |
| Predicate | smokeEvacuation |
P167615
|
FINISHED |
| Object | through roof and wall gaps |
—
|
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: through roof and wall gaps | Statement: [Savupirtti smoke cottage, smokeEvacuation, through roof and wall gaps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: smokeEvacuation Context triple: [Savupirtti smoke cottage, smokeEvacuation, through roof and wall gaps]
-
A.
smokeSystem
Indicates that an entity is equipped with or associated with a smoke-generating system (e.g., for signaling, testing, or special effects).
-
B.
smokestacks
Indicates the presence or involvement of smokestacks, typically as structures emitting smoke or exhaust as part of an industrial or energy-related process.
-
C.
smokeImpact
Indicates the effect or influence that smoke has on a target entity or condition.
-
D.
smokeLevel
Indicates the intensity or concentration of smoke present in or produced by an entity or environment.
-
E.
evacuationMethod
Indicates the means or procedure by which people or objects are removed from a place of danger or risk.
- 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_69f0d6266f8481909e70bb41cda18587 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f672b201048190b5265e1eec532ec4 |
completed | May 2, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69f6659f246081909821c5f452d14e8f |
completed | May 2, 2026, 8:59 p.m. |
| PDg | Predicate description generation | batch_69f6691da93081909deaf680614fc900 |
completed | May 2, 2026, 9:14 p.m. |
Created at: April 28, 2026, 7:21 p.m.