Triple
T24918930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chile Route CH-23 |
E624065
|
entity |
| Predicate | hasTerrainAlongRoute |
P103580
|
FINISHED |
| Object | mountainous |
—
|
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: mountainous | Statement: [Chile Route CH-23, hasTerrainAlongRoute, mountainous]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTerrainAlongRoute Context triple: [Chile Route CH-23, hasTerrainAlongRoute, mountainous]
-
A.
hasTerrainFor
Indicates that a location or area possesses terrain suitable or designated for a particular use, activity, or feature.
-
B.
involvesTerrain
chosen
Indicates that the relationship or action takes place in, across, or is directly affected by a specified type of terrain or landform.
-
C.
hasIntermediateTerrain
Indicates that something is situated on or characterized by terrain of medium or moderate difficulty or ruggedness, between easy/flat and difficult/extreme terrain.
-
D.
hasRockyTerrain
Indicates that the subject possesses or is characterized by rough, uneven, or rock-covered ground or surface conditions.
-
E.
terrainNavigation
Indicates the ability or process of moving through, over, or across different types of terrain or ground conditions.
- 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_69e2fac889c081908e9ff686cb428e5a |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f55e519978819087a1676564a74630 |
completed | May 2, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69f4a0edd10c81908a052ab864d57c54 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 18, 2026, 5:28 a.m.