Triple
T2345415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coastal Range (Chile) |
E45118
|
entity |
| Predicate | hasLandforms |
P940
|
FINISHED |
| Object | steep coastal slopes |
—
|
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: steep coastal slopes | Statement: [Coastal Range (Chile), hasLandforms, steep coastal slopes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandforms Context triple: [Coastal Range (Chile), hasLandforms, steep coastal slopes]
-
A.
hasLandform
chosen
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
B.
hasLandscapeFeatures
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
-
C.
hasNaturalFeature
Indicates that one entity possesses, contains, or is characterized by a particular natural feature (such as a mountain, river, forest, or coastline).
-
D.
terrainFeature
Indicates a relationship where one entity is a natural or constructed landform or surface characteristic associated with a given location or area.
-
E.
geologicalFormation
Indicates that one entity is a geological structure or feature that characterizes or composes the physical makeup of another entity.
- 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_69a88917935081909b755dbf38e81024 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abcade3c808190ab3803538ccbe620 |
completed | March 7, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_69abc59616a8819099711834e6f1ccd6 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:52 p.m.