Triple
T30913628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terrain Response |
E787521
|
entity |
| Predicate | terrainMode |
P170287
|
FINISHED |
| Object | General driving |
—
|
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: General driving | Statement: [Terrain Response, terrainMode, General driving]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terrainMode Context triple: [Terrain Response, terrainMode, General driving]
-
A.
terrainStyle
Indicates the characteristic type or pattern of terrain associated with an entity or location.
-
B.
terrainFeature
Indicates a relationship where one entity is a natural or constructed landform or surface characteristic associated with a given location or area.
-
C.
terrainNavigation
Indicates the ability or process of moving through, over, or across different types of terrain or ground conditions.
-
D.
terrainIncludes
Indicates that a specified terrain area contains or encompasses another geographic or environmental feature within its boundaries.
-
E.
terrainSpecialization
Indicates a relationship where an entity is particularly adapted or optimized for operation, performance, or use within a specific type of terrain.
- 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_69f224be300c8190a6513ce1ee0a7026 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69285fed48190b1eb55ff27eec20b |
completed | May 3, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69f68b7ec098819080480998038de940 |
completed | May 2, 2026, 11:40 p.m. |
| PDg | Predicate description generation | batch_69f68c517f308190873c1c7e05a0c6d0 |
completed | May 2, 2026, 11:44 p.m. |
Created at: April 29, 2026, 8:51 p.m.