Triple
T6675109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luna 9 |
E151829
|
entity |
| Predicate | landingTechnique |
P14975
|
FINISHED |
| Object | airbag-assisted landing |
—
|
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: airbag-assisted landing | Statement: [Luna 9, landingTechnique, airbag-assisted landing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: landingTechnique Context triple: [Luna 9, landingTechnique, airbag-assisted landing]
-
A.
landingMethod
chosen
Indicates the manner or technique by which something or someone arrives and comes to rest at a destination, typically from the air or space.
-
B.
plannedLandingMethod
Indicates that an entity has designated a specific method or procedure to be used for its landing.
-
C.
typeOfLanding
Indicates the specific kind or category of landing that occurs in a given event or situation.
-
D.
landingMass
Indicates the mass of an object or vehicle at the moment it lands.
-
E.
landingDistance
Indicates the required or actual distance needed for an aircraft or object to complete a landing from approach to full stop.
- 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_69c687f830bc81909eb8b04dbb8450b1 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c0aa8c5c8190a302b261f11b70cb |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6ad0b6d00819086205b8ce30dd045 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:03 p.m.