Triple
T15875328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giant Ledge |
E384938
|
entity |
| Predicate | numberOfMainViewpoints |
P86634
|
FINISHED |
| Object | several distinct ledge 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: several distinct ledge viewpoints | Statement: [Giant Ledge, numberOfMainViewpoints, several distinct ledge viewpoints]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMainViewpoints Context triple: [Giant Ledge, numberOfMainViewpoints, several distinct ledge viewpoints]
-
A.
hasMajorViewpoint
Indicates that an entity holds, expresses, or is characterized by a primary or dominant perspective, opinion, or stance on a subject.
-
B.
isMajorViewpointOf
Indicates that a particular perspective, opinion, or interpretation is a primary or widely recognized way of viewing or understanding something.
-
C.
numberOfPOVCharacters
Indicates the total count of distinct point-of-view characters associated with a given narrative or work.
-
D.
notableViewpoints
Indicates that an entity is associated with significant or noteworthy viewpoints, perspectives, or opinions.
-
E.
numberOfMainElements
chosen
Indicates the quantity of primary or central elements associated with an entity or structure.
- 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142c3e18c8190bb7b023f4a0eaebb |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:51 a.m.