Triple
T519585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Sinai |
E10782
|
entity |
| Predicate | hasViewOnTop |
P854
|
FINISHED |
| Object | sunrise over Sinai Peninsula |
—
|
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: sunrise over Sinai Peninsula | Statement: [Mount Sinai, hasViewOnTop, sunrise over Sinai Peninsula]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasViewOnTop Context triple: [Mount Sinai, hasViewOnTop, sunrise over Sinai Peninsula]
-
A.
hasView
chosen
Indicates that one entity provides a visual perspective or outlook onto another entity or scene.
-
B.
hasPositionOn
Indicates that one entity occupies or holds a specific role, job, or spatial location relative to another entity.
-
C.
hasTopLevel
Indicates that one entity is the highest or primary element within a hierarchy or structure relative to another entity.
-
D.
isToppedWith
Indicates that one entity serves as a topping placed on the surface of another entity.
-
E.
hasViewingSide
Indicates that one entity serves as the side or surface of another entity that is intended to be viewed or observed.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1a00a6c8190a62dc7c901c2f2ff |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f016ba5c81909825b04e7525b4ab |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.