Triple
T14998958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Horombo Hut |
E374031
|
entity |
| Predicate | nearbyVegetation |
P953
|
FINISHED |
| Object | giant groundsels and lobelias |
—
|
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: giant groundsels and lobelias | Statement: [Horombo Hut, nearbyVegetation, giant groundsels and lobelias]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyVegetation Context triple: [Horombo Hut, nearbyVegetation, giant groundsels and lobelias]
-
A.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
-
B.
vegetationType
chosen
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
C.
hasNearbyForestType
Indicates that one entity is located close to, or in the vicinity of, a forest of a specified type.
-
D.
hasNearbyLandscapeType
Indicates that one entity is located close to, or in the vicinity of, a particular type of landscape.
-
E.
hasAttractiveFoliage
Indicates that an entity possesses foliage that is visually appealing or ornamental in appearance.
- 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded71a5618819083ae96a79735ef98 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a6169b48190a679609febd2d0e3 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:54 a.m.