Triple
T1918324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Museum of Saudi Arabia |
E40068
|
entity |
| Predicate | numberOfExhibitionHalls |
P2490
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [National Museum of Saudi Arabia, numberOfExhibitionHalls, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfExhibitionHalls Context triple: [National Museum of Saudi Arabia, numberOfExhibitionHalls, 8]
-
A.
numberOfHalls
chosen
Indicates the quantity of halls associated with a given entity or location.
-
B.
numberOfExhibits
Indicates the total count of exhibits associated with a given entity or context.
-
C.
numberOfPavilions
Indicates the total count of pavilions associated with a given entity or context.
-
D.
hasExhibitionArea
Indicates that an entity includes or provides a designated space or area for exhibitions or displays.
-
E.
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.
- 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_69a8864298748190a2f2fd34f7ef8d77 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb2107fe48190bafff825f1f805ad |
completed | March 7, 2026, 5:05 a.m. |
| PD | Predicate disambiguation | batch_69abafed2ab481908920334e77b1021b |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.