Triple
T3992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolitan Museum of Art |
E75
|
entity |
| Predicate | significance |
P428
|
FINISHED |
| Object | one of the largest art museums in the world |
—
|
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: one of the largest art museums in the world | Statement: [Metropolitan Museum of Art, significance, one of the largest art museums in the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: significance Context triple: [Metropolitan Museum of Art, significance, one of the largest art museums in the world]
-
A.
significantEvent
Indicates that an event involving the entities is of notable importance or impact within a given context.
-
B.
signature
Indicates that one entity has provided an official or personal signed endorsement, authorization, or acknowledgment on or for another entity.
-
C.
symbolizes
Indicates that one entity stands for, represents, or is used as a sign for another entity, concept, or idea.
-
D.
purpose
Indicates that one entity exists, is done, or is used in order to achieve, support, or serve the goal, function, or intended outcome of another entity.
-
E.
status
Indicates the current condition, state, or standing of an entity within a given context.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69a23bcb4bbc819093775f623998d62d |
completed | Feb. 28, 2026, 12:50 a.m. |
Created at: Feb. 28, 2026, 12:40 a.m.