Triple
T3981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolitan Museum of Art |
E75
|
entity |
| Predicate | style |
P87
|
FINISHED |
| Object | Beaux-Arts architecture |
—
|
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: Beaux-Arts architecture | Statement: [Metropolitan Museum of Art, style, Beaux-Arts architecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: style Context triple: [Metropolitan Museum of Art, style, Beaux-Arts architecture]
-
A.
theme
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
-
B.
appearance
Indicates how something looks or seems to an observer, including its visible form, condition, or outward impression.
-
C.
format
Indicates the specific arrangement, structure, or presentation style in which something is organized or expressed.
-
D.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
-
E.
category
chosen
Indicates that one entity is classified as a member or type within the grouping or class defined 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_69a238d6b47881909e68288aed2fd858 |
completed | Feb. 28, 2026, 12:37 a.m. |
| NER | Named-entity recognition | batch_69a23bcc8eb48190b897cc331563980a |
completed | Feb. 28, 2026, 12:50 a.m. |
| PD | Predicate disambiguation | batch_69a23994309081909ff3e869deef2156 |
completed | Feb. 28, 2026, 12:40 a.m. |
Created at: Feb. 28, 2026, 12:40 a.m.