Triple
T18658719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tabarka |
E456133
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Jendouba |
—
|
NE NERFINISHED |
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: Jendouba | Statement: [Tabarka, nearbyCity, Jendouba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jendouba Context triple: [Tabarka, nearbyCity, Jendouba]
-
A.
Jendouba
chosen
Jendouba is a city in northwestern Tunisia known as an important regional center for agriculture and trade.
-
B.
El Kef
El Kef is a historic city in northwestern Tunisia known for its hilltop medina, Ottoman-era fortifications, and views over the surrounding mountains.
-
C.
Tahannaout
Tahannaout is a small town in central Morocco that serves as an administrative and market hub for the surrounding rural communities in the foothills of the High Atlas Mountains.
-
D.
Benslimane
Benslimane is a town and provincial capital in northwestern Morocco, known for its forests and proximity to Casablanca.
-
E.
Sidi Bennour
Sidi Bennour is a town and provincial capital in western Morocco known for its agricultural activities, particularly cereal and sugar beet production.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38ea1e88190997e9b231190ba6f |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e55087ae8081909cb4c0ce6c809d55 |
completed | April 19, 2026, 10 p.m. |
Created at: April 10, 2026, 11:48 a.m.