Triple
T3449651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dzyarzhynskaya Hara |
E72761
|
entity |
| Predicate | isNaturalOrArtificial |
P10299
|
FINISHED |
| Object | natural |
—
|
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: natural | Statement: [Dzyarzhynskaya Hara, isNaturalOrArtificial, natural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNaturalOrArtificial Context triple: [Dzyarzhynskaya Hara, isNaturalOrArtificial, natural]
-
A.
naturalOrArtificial
chosen
Indicates that something is classified as either naturally occurring or artificially created.
-
B.
isArtificial
Indicates that an entity is man-made or produced by human design rather than occurring naturally.
-
C.
isNaturalFiber
Indicates that a material or textile is made from fibers derived from natural sources rather than synthetic ones.
-
D.
hasNature
Indicates that something possesses, exhibits, or is characterized by a particular inherent quality, essence, or fundamental type.
-
E.
hasPhysicalNature
Indicates that one entity possesses or exhibits a specific physical form, composition, or material nature in relation to another.
- 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_69ad85b05c848190b7a28ceec2bd7b74 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adba71f4a4819089d08b871cc9b16f |
completed | March 8, 2026, 6:05 p.m. |
| PD | Predicate disambiguation | batch_69adae0255b48190a9069f7871c7a012 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:16 p.m.