Triple
T6784409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Algerian Air Force |
E155763
|
entity |
| Predicate | headquartersLocation |
P62
|
FINISHED |
| Object | Algiers |
E10377
|
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: Algiers | Statement: [Algerian Air Force, headquartersLocation, Algiers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Algiers Context triple: [Algerian Air Force, headquartersLocation, Algiers]
-
A.
Algiers
chosen
Algiers is the capital and largest city of Algeria, a major political, economic, and cultural center on the Mediterranean coast of North Africa.
-
B.
Tunis
Tunis is the capital and largest city of Tunisia, serving as a major political, economic, and cultural center in the Arab world.
-
C.
Berrechid
Berrechid is a rapidly growing city in northwestern Morocco known as an important agricultural and industrial hub within the Casablanca-Settat region.
-
D.
Benslimane
Benslimane is a town and provincial capital in northwestern Morocco, known for its forests and proximity to Casablanca.
-
E.
Tlemcen
Tlemcen is a historic city in northwestern Algeria known for its rich Islamic heritage, medieval architecture, and role as a major cultural and commercial center in the Maghreb.
- 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_69c688162bf8819088b664b5c3b5be7a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d28bdc3c8190aa60616d89db66ed |
completed | March 27, 2026, 6:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c72f8c0a3481909f33d2252cc1860c |
completed | March 28, 2026, 1:31 a.m. |
Created at: March 27, 2026, 2:14 p.m.