Triple
T29440881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seven Sisters Falls |
E746706
|
entity |
| Predicate | viewingSafety |
P107580
|
FINISHED |
| Object | viewed from designated viewpoints |
—
|
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: viewed from designated viewpoints | Statement: [Seven Sisters Falls, viewingSafety, viewed from designated viewpoints]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewingSafety Context triple: [Seven Sisters Falls, viewingSafety, viewed from designated viewpoints]
-
A.
viewingIs
Indicates that one entity is engaged in the act or state of viewing, observing, or watching another entity.
-
B.
observationSafety
Indicates that an observation or monitoring activity is conducted in a manner that ensures the safety of the subjects, observers, and environment involved.
-
C.
safetyDepiction
Indicates a relationship where something visually represents or illustrates aspects of safety, such as safe behavior, conditions, or precautions.
-
D.
safetySetting
Indicates that an entity is configured with a particular safety-related parameter, mode, or constraint governing how it operates or behaves.
-
E.
safetyContext
chosen
Indicates the circumstances, conditions, or environment that affect how safe an action, object, or situation is.
- 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_69f0a7a180e48190ae775e40047dbcb5 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f66b1c118881908d2cbbf894a0a1ce |
completed | May 2, 2026, 9:22 p.m. |
| PD | Predicate disambiguation | batch_69f66339175c819080bd70f0ff7057b1 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 3:22 p.m.