Triple
T38702702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Peak |
E950181
|
entity |
| Predicate | scenicCharacter |
P158007
|
FINISHED |
| Object | scenic |
—
|
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: scenic | Statement: [First Peak, scenicCharacter, scenic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scenicCharacter Context triple: [First Peak, scenicCharacter, scenic]
-
A.
scenicDescription
Indicates a descriptive portrayal of the visual or aesthetic qualities of a scene or landscape.
-
B.
scenicCategory
chosen
Indicates the classification of a place or route based on its visual appeal or scenic qualities.
-
C.
touristCharacter
Indicates that an entity has the role, behavior, or qualities characteristic of a tourist in relation to another entity or context.
-
D.
thematicCharacter
Indicates that an entity serves as a central or recurring figure embodying key themes or motifs within a narrative or discourse.
-
E.
spatialCharacter
Indicates a relationship where an entity is characterized or defined by a particular spatial property, configuration, or arrangement.
- 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_69f76f0124408190bb39c3040734846b |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:33 p.m.