Triple
T16606808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dak’Art |
E403464
|
entity |
| Predicate | typicalVenuesInclude |
P25526
|
FINISHED |
| Object | museums in Dakar |
—
|
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: museums in Dakar | Statement: [Dak’Art, typicalVenuesInclude, museums in Dakar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalVenuesInclude Context triple: [Dak’Art, typicalVenuesInclude, museums in Dakar]
-
A.
typicalVenues
chosen
Indicates that the specified locations are common or standard places where the associated activity, event, or entity usually occurs or is hosted.
-
B.
typicalVenueSetting
Indicates the usual or characteristic type of venue or setting in which an event, activity, or interaction typically takes place.
-
C.
formerTypicalVenue
Indicates that a location was once the usual or primary venue for an entity’s activities or events, but no longer serves in that typical role.
-
D.
typicalVenueMetroArea
Indicates the metropolitan area where an entity is most commonly or characteristically located or hosted.
-
E.
primaryVenues
Indicates the main or most important venues associated with or used by a given entity.
- 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e36091de048190b40aa42b1a0681cc |
completed | April 18, 2026, 10:44 a.m. |
| PD | Predicate disambiguation | batch_69e296aabc508190b3836a91b49113ad |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:17 a.m.