Triple
T13697450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wasalu Jaco |
E328421
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Wasalu |
E331453
|
NE 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: Wasalu | Statement: [Wasalu Jaco, givenName, Wasalu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wasalu Context triple: [Wasalu Jaco, givenName, Wasalu]
-
A.
Wasalu
chosen
Wasalu is the given first name of American rapper, songwriter, and record producer Lupe Fiasco.
-
B.
Songololo
Songololo is a town in the western Democratic Republic of the Congo, situated near the border with Angola and known as a local transport and trade hub.
-
C.
Shalateen
Shalateen is a remote Egyptian town near the Sudanese border, known for its Bedouin communities, camel markets, and strategic location along the Red Sea coast.
-
D.
Sindalah
Sindalah is a luxury island destination in Saudi Arabia’s NEOM mega-development, designed as an exclusive hub for high-end tourism, yachting, and leisure on the Red Sea.
-
E.
Lasalimu
Lasalimu is a coastal town and district in Southeast Sulawesi, Indonesia, known as a local administrative and transit area in the region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc878b57c819094e7ea6d1a64211f |
completed | April 12, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79453395481909d651cb3a128f23d |
completed | May 3, 2026, 6:30 p.m. |
Created at: April 9, 2026, 9:54 p.m.