Triple
T19718173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Public Library Stephen A. Schwarzman Building main entrance |
E473533
|
entity |
| Predicate | frequentlyPhotographedAs |
P17748
|
FINISHED |
| Object | New York City landmark |
—
|
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: New York City landmark | Statement: [New York Public Library Stephen A. Schwarzman Building main entrance, frequentlyPhotographedAs, New York City landmark]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequentlyPhotographedAs Context triple: [New York Public Library Stephen A. Schwarzman Building main entrance, frequentlyPhotographedAs, New York City landmark]
-
A.
oftenPhotographedAt
chosen
Indicates that an entity is frequently the subject of photographs taken at a particular location or during a specific event.
-
B.
photographedByTourists
Indicates that the subject has been photographed by people visiting as tourists.
-
C.
photographsTakenIn
Indicates that photographs were captured or taken within a specific location or place.
-
D.
wasPhotographedAs
Indicates that one entity appears in a photograph specifically portraying them in the role, character, or identity of another entity.
-
E.
famousImage
Indicates that an image is widely recognized or well-known, typically due to its prominence, popularity, or cultural significance.
- 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_69d8e516dd048190a0b6c93ea3e71f58 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6440ec9e881909b75c0ebefab827f |
completed | April 20, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69e530438c60819082364c7be3eef6f0 |
completed | April 19, 2026, 7:42 p.m. |
Created at: April 10, 2026, 1:46 p.m.