Triple
T544135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mogadishu |
E12694
|
entity |
| Predicate | historicalRegion |
P915
|
FINISHED |
| Object | Benadir |
E67895
|
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: Benadir | Statement: [Mogadishu, historicalRegion, Benadir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Benadir Context triple: [Mogadishu, historicalRegion, Benadir]
-
A.
Nasar
Nasar is a surname most notably associated with Sylvia Nasar, the economist and author of "A Beautiful Mind."
-
B.
Banaadir
chosen
Banaadir is a coastal region in southeastern Somalia that encompasses the capital city, Mogadishu, and serves as a key political and economic center of the country.
-
C.
L’Orient
L’Orient was a massive French ship of the line that served as Admiral Brueys’ flagship and was famously destroyed in a catastrophic explosion during the Battle of the Nile in 1798.
-
D.
Aeromar
Aeromar is a Mexican regional airline that primarily operates domestic and short-haul international flights, with a major operational base in Mexico City.
-
E.
Sranan
Sranan is an English- and Dutch-influenced creole language spoken primarily in Suriname.
- 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_69a49334226c81908b0ea1689ef6aa3f |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a498dea88881908a938fe8f2313bec |
completed | March 1, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4e3f3f4e08190a625ae085868b191 |
completed | March 2, 2026, 1:12 a.m. |
Created at: March 1, 2026, 7:32 p.m.