Triple
T7022641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North facade of the White House |
E162864
|
entity |
| Predicate | isFrequentlyDepictedIn |
P34220
|
FINISHED |
| Object | news photographs |
—
|
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: news photographs | Statement: [North facade of the White House, isFrequentlyDepictedIn, news photographs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFrequentlyDepictedIn Context triple: [North facade of the White House, isFrequentlyDepictedIn, news photographs]
-
A.
commonlyDepictedOn
chosen
Indicates that something is frequently shown or represented on the surface, medium, or context of another thing.
-
B.
oftenDepictedAs
Indicates that one entity is frequently represented or portrayed in the form, appearance, or symbolism of another entity.
-
C.
workOftenDepicts
Indicates that one entity’s work frequently portrays, represents, or includes the other entity as a subject or theme.
-
D.
hasCulturalDepiction
Indicates that one entity is represented, portrayed, or depicted in the cultural work or expression of another entity.
-
E.
depictsNotablePerson
Indicates that one entity visually represents or portrays a person who is considered notable or significant.
- 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_69c6885b26248190a857541e3d10e299 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e5ecd4488190bf19e42de55da98b |
completed | March 27, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69c6e1b8118481909d76eb6616160e80 |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:35 p.m.