Triple
T696945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Wall of China |
E13913
|
entity |
| Predicate | followsGeographicalFeature |
P3944
|
FINISHED |
| Object | mountain ridges |
—
|
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 ridges | Statement: [Great Wall of China, followsGeographicalFeature, mountain ridges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsGeographicalFeature Context triple: [Great Wall of China, followsGeographicalFeature, mountain ridges]
-
A.
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).
-
B.
followsWatercourse
Indicates that one entity runs alongside or traces the path of a watercourse such as a river, stream, or canal.
-
C.
hasGeographyCharacteristic
Indicates that an entity possesses a specific geographical feature, property, or attribute.
-
D.
hasNaturalFeature
Indicates that one entity possesses, contains, or is characterized by a particular natural feature (such as a mountain, river, forest, or coastline).
-
E.
featureOfInterest
Indicates the entity or object that is the primary subject or focus of the described observation, measurement, or analysis.
- 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_69a493406c408190957eeec9048a8fb6 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a0c8055881909565ebde2be8fd7a |
completed | March 1, 2026, 8:25 p.m. |
| PD | Predicate disambiguation | batch_69a49d2586b081908e052cc5ba1d2685 |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.