Triple

T9494391
Position Surface form Disambiguated ID Type / Status
Subject Ethiopian literature E228966 entity
Predicate notableAuthor P4290 FINISHED
Object Hama Tuma
Hama Tuma is an Ethiopian writer and political satirist known for his sharp, critical short stories and essays that challenge authoritarianism and social injustice.
 E802322 NE FINISHED

How this triple was built (4 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: Hama Tuma | Statement: [Ethiopian literature, notableAuthor, Hama Tuma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hama Tuma
Context triple: [Ethiopian literature, notableAuthor, Hama Tuma]
  • A. Hamutal
    Hamutal was a queen of Judah, known as the mother of the last king of Judah, Zedekiah, during the final years before the Babylonian exile.
  • B. Tarama
    Tarama is a small island municipality in Okinawa Prefecture, Japan, known for its subtropical climate, traditional Ryukyuan culture, and surrounding coral reefs.
  • C. Hamazi
    Hamazi was an ancient Mesopotamian city-state, likely located in the Zagros foothills, known from early Sumerian sources as a rival power in the region.
  • D. Tamambo
    Tamambo is an Oceanic Austronesian language spoken primarily on Malo Island in Vanuatu.
  • E. Tamalu
    Tamalu is a village located on Car Nicobar Island in the Nicobar district of India’s Andaman and Nicobar Islands.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hama Tuma
Triple: [Ethiopian literature, notableAuthor, Hama Tuma]
Generated description
Hama Tuma is an Ethiopian writer and political satirist known for his sharp, critical short stories and essays that challenge authoritarianism and social injustice.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hama Tuma
Target entity description: Hama Tuma is an Ethiopian writer and political satirist known for his sharp, critical short stories and essays that challenge authoritarianism and social injustice.
  • A. Hamutal
    Hamutal was a queen of Judah, known as the mother of the last king of Judah, Zedekiah, during the final years before the Babylonian exile.
  • B. Tarama
    Tarama is a small island municipality in Okinawa Prefecture, Japan, known for its subtropical climate, traditional Ryukyuan culture, and surrounding coral reefs.
  • C. Hamazi
    Hamazi was an ancient Mesopotamian city-state, likely located in the Zagros foothills, known from early Sumerian sources as a rival power in the region.
  • D. Tamambo
    Tamambo is an Oceanic Austronesian language spoken primarily on Malo Island in Vanuatu.
  • E. Tamalu
    Tamalu is a village located on Car Nicobar Island in the Nicobar district of India’s Andaman and Nicobar Islands.
  • F. None of above. chosen

Provenance (5 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_69ca847424f081908180305555139f7a completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd95ea4a04819092c7842361c6296e completed April 1, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69d12d2e2a64819097d87b3cf304f036 completed April 4, 2026, 3:24 p.m.
NEDg Description generation batch_69d12e20f4ac8190bd6aef228f13689e completed April 4, 2026, 3:28 p.m.
NED2 Entity disambiguation (via description) batch_69d12eae212481908f2136966fca8df5 completed April 4, 2026, 3:30 p.m.
Created at: March 30, 2026, 7:56 p.m.