Triple
T2153109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zintan militias |
E47825
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Zintan |
E244674
|
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: Zintan | Statement: [Zintan militias, locatedIn, Zintan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zintan Context triple: [Zintan militias, locatedIn, Zintan]
-
A.
Zintan
chosen
Zintan is a town in western Libya known for its role in the Libyan Civil War and for being controlled by powerful local militias.
-
B.
Kassala
Kassala is a city in eastern Sudan near the Eritrean border, known as a regional trade center and for its striking granite hills and cultural diversity.
-
C.
Omdurman
Omdurman is a major city in Sudan, historically significant as a cultural and commercial center and effectively forming part of the country’s greater capital area.
-
D.
Dongola
Dongola is a historic town in northern Sudan that served as a major political and cultural center of medieval Nubian kingdoms along the Nile.
-
E.
Ibb
Ibb is a city in southwestern Yemen known for its lush green landscapes, mild climate, and historical architecture.
- 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_69a88a1d1fd8819088b34990d69a712f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe4a3b608190b3bd5d8e28534090 |
completed | March 7, 2026, 5:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71af0fa081909dd4b2a7452623da |
completed | March 9, 2026, 7:07 a.m. |
Created at: March 4, 2026, 7:44 p.m.