Triple
T135943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pan-American Highway |
E2745
|
entity |
| Predicate | traversesTerrain |
P3944
|
FINISHED |
| Object | mountain ranges |
—
|
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: mountain ranges | Statement: [Pan-American Highway, traversesTerrain, mountain ranges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traversesTerrain Context triple: [Pan-American Highway, traversesTerrain, mountain ranges]
-
A.
hasLandform
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
B.
brokeGround
Indicates that an entity initiated construction or development on a site, typically by starting physical work such as excavation or foundation laying.
-
C.
followsNaturalFeature
chosen
Indicates that one entity’s position, path, or boundary runs alongside or is aligned with a natural geographic feature (such as a river, coastline, or ridgeline).
-
D.
previousGround
Indicates that one entity is the immediately preceding ground or surface state relative to another in a sequence or progression.
-
E.
hasGroundTransportation
Indicates that an entity provides, includes, or is connected to transportation services or options that operate on land (e.g., cars, buses, trains).
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a4edf081908c494c8370c76b9a |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a25651b9048190a6277b7fec98c1ea |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.