Triple
T16573026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skunk Train |
E402635
|
entity |
| Predicate | sceneryFeature |
P61635
|
FINISHED |
| Object | coastal redwood trees |
—
|
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: coastal redwood trees | Statement: [Skunk Train, sceneryFeature, coastal redwood trees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sceneryFeature Context triple: [Skunk Train, sceneryFeature, coastal redwood trees]
-
A.
scenicDescription
Indicates a descriptive portrayal of the visual or aesthetic qualities of a scene or landscape.
-
B.
terrainFeature
Indicates a relationship where one entity is a natural or constructed landform or surface characteristic associated with a given location or area.
-
C.
sceneFeature
chosen
Indicates a characteristic, element, or attribute that is present within or helps define a particular scene.
-
D.
isPartOfScenicVista
Indicates that something is included within, or contributes to, a larger scenic vista or panoramic view.
-
E.
landscapeElement
Indicates that one entity functions as a landscape-related feature or component in relation to 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_69d8838648088190acf97ef11fc3f61b |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3595ab9dc81909b774f6d9c17d6dd |
completed | April 18, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69e296a47b7481909d9958158510c806 |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:16 a.m.