Triple
T7533630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tunisian Saharan Berber |
E178089
|
entity |
| Predicate | branchOf |
P479
|
FINISHED |
| Object | Zenati |
E180475
|
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: Zenati | Statement: [Tunisian Saharan Berber, branchOf, Zenati]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zenati Context triple: [Tunisian Saharan Berber, branchOf, Zenati]
-
A.
Zenati
chosen
Zenati is a branch of the Northern Berber languages spoken in North Africa, encompassing several closely related dialect groups.
-
B.
Atessa
Atessa is a town and municipality in the Abruzzo region of central Italy, known for its industrial activity and automotive manufacturing facilities.
-
C.
Tianeti
Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
-
D.
Enodia
Enodia is an epithet of the Greek goddess Hecate that emphasizes her role as a protector and guide along roads, thresholds, and liminal spaces.
-
E.
Zayton
Zayton is the historical name used by medieval Arab and European traders for the major Chinese port city of Quanzhou, once one of the world’s busiest maritime trade centers.
- 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_69c69f2acdbc8190b5a8320168c1d0ba |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8493964819086aeddfa4872a70b |
completed | March 27, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c84f0765b48190b8df68f22c8901f4 |
completed | March 28, 2026, 9:58 p.m. |
Created at: March 27, 2026, 3:47 p.m.