Triple
T22477446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boeing 737 MAX |
E555670
|
entity |
| Predicate | safetyControversy |
P42781
|
FINISHED |
| Object | MCAS behavior and sensor redundancy |
—
|
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: MCAS behavior and sensor redundancy | Statement: [Boeing 737 MAX, safetyControversy, MCAS behavior and sensor redundancy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyControversy Context triple: [Boeing 737 MAX, safetyControversy, MCAS behavior and sensor redundancy]
-
A.
controversy
Indicates a situation in which there is active disagreement, dispute, or public debate between parties over a particular issue, action, or claim.
-
B.
controversyType
chosen
Indicates the specific kind or category of controversy associated with an entity or situation.
-
C.
controversialBecause
Indicates that one entity is considered controversial specifically due to, or as a result of, its relationship with or association to another entity.
-
D.
locationOfControversy
Indicates the place or setting where a dispute, debate, or controversy occurs or is centered.
-
E.
controversialStatus
Indicates that the subject is associated with debate, dispute, or disagreement regarding its acceptance, validity, or appropriateness.
- 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_69e11e52c2048190952dc5df209b9bed |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15be58ed08190b88706a7cb85616b |
completed | April 29, 2026, 1:16 a.m. |
| PD | Predicate disambiguation | batch_69e898b6eee08190ba673a0ee329e671 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:49 p.m.