Triple

T5804745
Position Surface form Disambiguated ID Type / Status
Subject Task Force Ranger E128715 entity
Predicate location P40 FINISHED
Object Mogadishu E12694 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: Mogadishu | Statement: [Task Force Ranger, location, Mogadishu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mogadishu
Context triple: [Task Force Ranger, location, Mogadishu]
  • A. Mogadishu chosen
    Mogadishu is the capital and largest city of Somalia, serving as a major political, economic, and cultural center on the Horn of Africa.
  • B. Hargeisa
    Hargeisa is the largest city and political, economic, and cultural center of the self-declared republic of Somaliland in the Horn of Africa.
  • C. Port of Mogadishu
    The Port of Mogadishu is Somalia’s principal seaport and a key hub for the country’s maritime trade on the Indian Ocean.
  • D. Burao
    Burao is a key commercial and administrative city in central Somaliland, known as a major livestock trading hub in the region.
  • E. Djibouti City
    Djibouti City is the largest urban center and main economic, political, and cultural hub of the Republic of Djibouti, located on the Gulf of Tadjoura in the Horn of Africa.
  • 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_69c00846a0d881909e46841f8e156b64 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02b1461a48190be2042dd3823d02e completed March 22, 2026, 5:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c09836d00881908c210b2932d67519 completed March 23, 2026, 1:32 a.m.
Created at: March 22, 2026, 3:52 p.m.