Triple
T4733044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Béja Governorate |
E105056
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Béja |
E482988
|
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: Béja | Statement: [Béja Governorate, hasCity, Béja]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Béja Context triple: [Béja Governorate, hasCity, Béja]
-
A.
Béja
chosen
Béja is a historic city in northwestern Tunisia known for its agricultural importance and Roman-era heritage.
-
B.
Guellala
Guellala is a traditional pottery-making village on the Tunisian island of Djerba, known for its distinctive ceramics and cultural heritage.
-
C.
Larache
Larache is a coastal city in northwestern Morocco, situated along the Atlantic Ocean and known for its historic medina and nearby ancient Phoenician-Roman archaeological site of Lixus.
-
D.
Settat
Settat is a city in western Morocco located between Casablanca and Marrakech, known as a regional agricultural and commercial center.
-
E.
Tachelhit
Tachelhit is a Berber (Amazigh) language spoken primarily in southwestern Morocco, especially in the Souss region and the High Atlas mountains.
- 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_69bd43ee52048190b81a4f066534ffb3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6466354481908595f5bb56025cdb |
completed | March 20, 2026, 3:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be89c899f08190bb8227b13a90185d |
completed | March 21, 2026, 12:06 p.m. |
Created at: March 20, 2026, 1:19 p.m.