Triple
T1338168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Night Watch Gallery |
E28402
|
entity |
| Predicate | museumCategory |
P18644
|
FINISHED |
| Object | art museum gallery |
—
|
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: art museum gallery | Statement: [Night Watch Gallery, museumCategory, art museum gallery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: museumCategory Context triple: [Night Watch Gallery, museumCategory, art museum gallery]
-
A.
museumFocus
chosen
Indicates that a museum is primarily dedicated to or specializes in a particular subject, theme, or type of collection.
-
B.
museumSection
Indicates that one entity is a section, area, or subdivision within a museum associated with the other entity.
-
C.
majorMuseum
Indicates that a museum holds significant importance or prominence, typically due to its size, collections, reputation, or cultural impact.
-
D.
museumAt
Indicates that an entity (such as an exhibit, artifact, or event) is located at or associated with a particular museum.
-
E.
museumCity
Indicates the city in which a given museum is located.
- 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_69a49854eb3481908c7d56b2e449a290 |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c2115d388190b031ae2de1296f8a |
completed | March 1, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69a4bef174708190a07bbc697fe19a2d |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:56 p.m.