Triple
T37969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Museum of Modern Art |
E751
|
entity |
| Predicate | hasCollectionSize |
P425
|
FINISHED |
| Object | over 200000 works |
—
|
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: over 200000 works | Statement: [Museum of Modern Art, hasCollectionSize, over 200000 works]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCollectionSize Context triple: [Museum of Modern Art, hasCollectionSize, over 200000 works]
-
A.
hasCollection
Indicates that an entity possesses, maintains, or is associated with a set or group of related items treated as a collection.
-
B.
hasCollectionType
Indicates that an entity is associated with or organized under a specific type or category of collection.
-
C.
collectionSize
chosen
Indicates the total number of items contained within a specified collection.
-
D.
hasCollectionFocus
Indicates that something is primarily concerned with, centered on, or directed toward a particular collection or set of items.
-
E.
hasSectionCount
Indicates that an entity is associated with a specific number of sections it contains or comprises.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24b4d5bd08190a3a48eb26e67768c |
completed | Feb. 28, 2026, 1:56 a.m. |
| PD | Predicate disambiguation | batch_69a24ab6141881908701106aa97e4735 |
completed | Feb. 28, 2026, 1:53 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.