Triple
T11571447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | balancing rocks |
E274394
|
entity |
| Predicate | haveVisualImpact |
P17691
|
FINISHED |
| Object | striking and unusual landscapes |
—
|
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: striking and unusual landscapes | Statement: [balancing rocks, haveVisualImpact, striking and unusual landscapes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveVisualImpact Context triple: [balancing rocks, haveVisualImpact, striking and unusual landscapes]
-
A.
hasImpactScale
Indicates the degree or magnitude of impact that one entity or action has on another, typically expressed along a defined scale.
-
B.
recognizesImpactOn
Indicates that one entity acknowledges or understands the effect or consequences it has on another entity or situation.
-
C.
hasImpactFocus
Indicates that an entity is primarily concerned with or directed toward a particular type or area of impact.
-
D.
hasNotableImpact
chosen
Indicates that one entity exerts a significant or noteworthy influence or effect on another entity or context.
-
E.
hasLocalImpact
Indicates that an entity produces effects or consequences within a specific local area or community.
- 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_69d6aae5ac3c81908d2b0a3a665665b2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d88dd6913881908becf188c0a7a275 |
completed | April 10, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69d85dcbacd0819094d4a1237055affa |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:38 p.m.