Triple
T1473106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mit Rahina museum area |
E27179
|
entity |
| Predicate | hasOutdoorExhibits |
P29093
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Mit Rahina museum area, hasOutdoorExhibits, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOutdoorExhibits Context triple: [Mit Rahina museum area, hasOutdoorExhibits, true]
-
A.
hasIndoorExhibits
Indicates that an entity provides or contains exhibits that are located indoors.
-
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.
hasOnsiteMuseumOrExhibits
Indicates that a place includes an on-site museum or exhibit area available for visitors.
-
D.
hasInteractiveExhibits
Indicates that something contains exhibits designed for active participation or engagement by the audience.
-
E.
hasExhibitionArea
Indicates that an entity includes or provides a designated space or area for exhibitions or displays.
- 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_69a496d25d6881909dbd84f86d763992 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c5dc90e481908a4935f266bc7850 |
completed | March 1, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69a4c48350d88190a81bd149103f93e3 |
completed | March 1, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69a4c52bbb748190aaa804438d31f4c2 |
completed | March 1, 2026, 11 p.m. |
Created at: March 1, 2026, 8:01 p.m.