Triple
T239162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Ontario Museum |
E4889
|
entity |
| Predicate | hasExhibitionArea |
P9481
|
FINISHED |
| Object | over 40 galleries |
—
|
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 40 galleries | Statement: [Royal Ontario Museum, hasExhibitionArea, over 40 galleries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExhibitionArea Context triple: [Royal Ontario Museum, hasExhibitionArea, over 40 galleries]
-
A.
hasExhibition
Indicates that an entity organizes, hosts, or presents a particular exhibition.
-
B.
hasExhibits
Indicates that an entity (such as a museum, gallery, or event) displays or presents certain items, artworks, or objects as part of its collection or show.
-
C.
hasInteractiveExhibits
Indicates that something contains exhibits designed for active participation or engagement by the audience.
-
D.
numberOfExhibits
Indicates the total count of exhibits associated with a given entity or context.
-
E.
hasArtGallery
Indicates that one entity possesses, contains, or hosts an art gallery as part of its facilities or offerings.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25dacf60c8190a5c3ef455b9a8b20 |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b5f27208190ae13f34037fe582b |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25dab745c8190829b7b5e915936e8 |
completed | Feb. 28, 2026, 3:14 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.