Triple

T1788921
Position Surface form Disambiguated ID Type / Status
Subject Lake Tana E39450 entity
Predicate hasIsland P970 FINISHED
Object Tana Qirqos
Tana Qirqos is a historically significant island in Ethiopia’s Lake Tana, known for its ancient Christian monastery and religious heritage.
E207669 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: Tana Qirqos | Statement: [Lake Tana, hasIsland, Tana Qirqos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tana Qirqos
Context triple: [Lake Tana, hasIsland, Tana Qirqos]
  • A. Yenakiieve
    Yenakiieve is an industrial city in eastern Ukraine, historically known for its coal mining and metallurgical industries.
  • B. Gorely
    Gorely is an active stratovolcano complex on Russia’s Kamchatka Peninsula, known for its multiple craters, frequent eruptions, and striking acidic crater lakes.
  • C. Aldan
    Aldan is a mining town in Russia’s Sakha Republic known for its significant gold deposits and remote Siberian location.
  • D. Argun
    Argun is a small city in the Chechen Republic of Russia, located just southeast of the regional capital Grozny.
  • E. Rishra
    Rishra is an industrial town and municipal area in the Hooghly district of West Bengal, India, known for its jute mills and proximity to Kolkata along the Hooghly River.
  • 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: Tana Qirqos
Triple: [Lake Tana, hasIsland, Tana Qirqos]
Generated description
Tana Qirqos is a historically significant island in Ethiopia’s Lake Tana, known for its ancient Christian monastery and religious heritage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tana Qirqos
Target entity description: Tana Qirqos is a historically significant island in Ethiopia’s Lake Tana, known for its ancient Christian monastery and religious heritage.
  • A. Yenakiieve
    Yenakiieve is an industrial city in eastern Ukraine, historically known for its coal mining and metallurgical industries.
  • B. Gorely
    Gorely is an active stratovolcano complex on Russia’s Kamchatka Peninsula, known for its multiple craters, frequent eruptions, and striking acidic crater lakes.
  • C. Aldan
    Aldan is a mining town in Russia’s Sakha Republic known for its significant gold deposits and remote Siberian location.
  • D. Argun
    Argun is a small city in the Chechen Republic of Russia, located just southeast of the regional capital Grozny.
  • E. Rishra
    Rishra is an industrial town and municipal area in the Hooghly district of West Bengal, India, known for its jute mills and proximity to Kolkata along the Hooghly River.
  • 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_69a88631854081909723959921e45c2b completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa65111e5481909c22abb6ad966814 completed March 6, 2026, 5:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69add1b8e26c8190af6e45265e2b182f completed March 8, 2026, 7:44 p.m.
NEDg Description generation batch_69add29b34048190bee7908ac6c650e4 completed March 8, 2026, 7:48 p.m.
NED2 Entity disambiguation (via description) batch_69add35731588190a13c969490ca2c09 completed March 8, 2026, 7:51 p.m.
Created at: March 4, 2026, 7:32 p.m.