Triple

T9606029
Position Surface form Disambiguated ID Type / Status
Subject National Resistance Movement E231973 entity
Predicate headquartersLocation P62 FINISHED
Object Kampala E40695 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: Kampala | Statement: [National Resistance Movement, headquartersLocation, Kampala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kampala
Context triple: [National Resistance Movement, headquartersLocation, Kampala]
  • A. Kampala chosen
    Kampala is the capital and largest city of Uganda, serving as the country’s political, economic, and cultural center.
  • B. Entebbe
    Entebbe is a town in central Uganda on a peninsula into Lake Victoria, known for its international airport and the site of the 1976 hostage-rescue operation.
  • C. Dodoma
    Dodoma is the political and administrative capital city of Tanzania, located in the country’s central region.
  • D. Lipa City
    Lipa City is a highly urbanized city in Batangas, Philippines, known as a commercial, educational, and religious center in the Calabarzon region.
  • E. Kabete
    Kabete is a prominent town in Kenya’s Central Region, situated within Kiambu County and known for its agricultural activity and proximity to Nairobi.
  • 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_69ca8485a90c819094fe40b42fde9d70 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9a6006d48190adc03306533b9be6 completed April 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69d18205237c8190a6e7b4009b512d6d completed April 4, 2026, 9:26 p.m.
Created at: March 30, 2026, 8:08 p.m.