Triple

T16442916
Position Surface form Disambiguated ID Type / Status
Subject Gedo E399348 entity
Predicate containsCity P294 FINISHED
Object Bardera E1212950 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: Bardera | Statement: [Gedo, containsCity, Bardera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bardera
Context triple: [Gedo, containsCity, Bardera]
  • A. Bardera chosen
    Bardera is a major Somali city in the Gedo region, serving as an important commercial and administrative center in southwestern Somalia.
  • B. Banyole
    The Banyole are a Bantu-speaking ethnic group in eastern Uganda known for their agricultural livelihoods, clan-based social structure, and rich oral traditions.
  • C. Berbera
    Berbera is a major port city on the Gulf of Aden in Somaliland, serving as a key maritime hub for trade in the Horn of Africa.
  • D. Bologhine
    Bologhine is a coastal district of Algiers, Algeria, known for its historic neighborhoods and proximity to the Mediterranean Sea.
  • E. Gambela
    Gambela is a town in western Ethiopia located near the Baro River, known as a trading center and gateway to the Gambela Region bordering South Sudan.
  • 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_69d87f2c6778819080fcfae53be8f12a completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32cd8d2988190acb5722a15623319 completed April 18, 2026, 7:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f4b738881908f8a205466397f33 completed May 10, 2026, 9:26 a.m.
Created at: April 10, 2026, 5:10 a.m.