Triple
T7829208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2020 Calabasas helicopter crash |
E181322
|
entity |
| Predicate | impactTerrain |
P78272
|
FINISHED |
| Object | hillside |
—
|
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: hillside | Statement: [2020 Calabasas helicopter crash, impactTerrain, hillside]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactTerrain Context triple: [2020 Calabasas helicopter crash, impactTerrain, hillside]
-
A.
terrainImpact
chosen
Indicates how the characteristics of the terrain influence or modify the outcome, behavior, or effectiveness of an action or interaction.
-
B.
impactTower
Indicates that one entity exerts a significant force or collision upon a tower-like structure, affecting its state or stability.
-
C.
terrainIncludes
Indicates that a specified terrain area contains or encompasses another geographic or environmental feature within its boundaries.
-
D.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
E.
terrainFeature
Indicates a relationship where one entity is a natural or constructed landform or surface characteristic associated with a given location or area.
- 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_69ca8282ccec819083c48efb72d21cf9 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb04aaed1881908e1da129a43ef9c7 |
completed | March 30, 2026, 11:18 p.m. |
| PD | Predicate disambiguation | batch_69cae91ae008819098e56bbe51143b31 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:44 p.m.