Triple
T15366083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guiana Highlands |
E367417
|
entity |
| Predicate | characteristicLandform |
P940
|
FINISHED |
| Object | tepui |
—
|
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: tepui | Statement: [Guiana Highlands, characteristicLandform, tepui]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characteristicLandform Context triple: [Guiana Highlands, characteristicLandform, tepui]
-
A.
physicalFeature
Indicates that one entity possesses or exhibits a particular physical characteristic or attribute.
-
B.
hasLandform
chosen
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
C.
topographicalCategory
Indicates the type of landform or surface feature that characterizes the physical terrain associated with an entity.
-
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.
landerType
Indicates the specific kind or category of lander involved in the relationship or action.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e497de48190be249b110999ec5c |
completed | April 16, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69deca9ab7e88190a9261ef27be665b1 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:18 a.m.