Triple
T5555496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Horseshoe Bend |
E145627
|
entity |
| Predicate | photographyPopularity |
P3033
|
FINISHED |
| Object | widely shared on social media |
—
|
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: widely shared on social media | Statement: [Horseshoe Bend, photographyPopularity, widely shared on social media]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: photographyPopularity Context triple: [Horseshoe Bend, photographyPopularity, widely shared on social media]
-
A.
popularFor
chosen
Indicates that something is widely liked, recognized, or favored specifically because of a particular feature, quality, or use.
-
B.
photographyGenre
Indicates the specific genre or style of photography that characterizes a photographic work or activity.
-
C.
oftenPhotographedAt
Indicates that an entity is frequently the subject of photographs taken at a particular location or during a specific event.
-
D.
peakPopularity
Indicates the time or context in which something reaches its highest level of popularity relative to other times or contexts.
-
E.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
- 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_69c008fcaf788190bafa02a1917ee73b |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01ffc5e7c81908e1c454d3bfd357b |
completed | March 22, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69c01b10bbf8819098655839c03b7832 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:36 p.m.