Triple

T13111832
Position Surface form Disambiguated ID Type / Status
Subject Gezira State E310990 entity
Predicate hasSettlement P1068 FINISHED
Object Managil
Managil is a town in Sudan’s Gezira State, known primarily as an agricultural center within the Gezira irrigation scheme.
E1023124 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: Managil | Statement: [Gezira State, hasSettlement, Managil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Managil
Context triple: [Gezira State, hasSettlement, Managil]
  • A. Manghit
    Manghit was a Central Asian tribal group that rose to prominence as the ruling clan of the Manghit (Bukhara) dynasty.
  • B. Mahinog
    Mahinog is a coastal municipality on Camiguin Island in the Philippines known for its rural communities and access to nearby islets and marine attractions.
  • C. Kalamansig
    Kalamansig is a coastal municipality in the province of Sultan Kudarat in the Philippines, known for its fishing industry and diverse indigenous communities.
  • D. Mangilao
    Mangilao is a village on the eastern side of Guam known for hosting the University of Guam and Guam Community College.
  • E. Matiltan
    Matiltan is a scenic valley and tourist spot near Kalam in Pakistan’s Swat region, known for its lush landscapes, rivers, and views of surrounding mountains.
  • 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: Managil
Triple: [Gezira State, hasSettlement, Managil]
Generated description
Managil is a town in Sudan’s Gezira State, known primarily as an agricultural center within the Gezira irrigation scheme.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Managil
Target entity description: Managil is a town in Sudan’s Gezira State, known primarily as an agricultural center within the Gezira irrigation scheme.
  • A. Manghit
    Manghit was a Central Asian tribal group that rose to prominence as the ruling clan of the Manghit (Bukhara) dynasty.
  • B. Mahinog
    Mahinog is a coastal municipality on Camiguin Island in the Philippines known for its rural communities and access to nearby islets and marine attractions.
  • C. Kalamansig
    Kalamansig is a coastal municipality in the province of Sultan Kudarat in the Philippines, known for its fishing industry and diverse indigenous communities.
  • D. Mangilao
    Mangilao is a village on the eastern side of Guam known for hosting the University of Guam and Guam Community College.
  • E. Matiltan
    Matiltan is a scenic valley and tourist spot near Kalam in Pakistan’s Swat region, known for its lush landscapes, rivers, and views of surrounding mountains.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9817e4f408190b77c198b4157d77a completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e27d8110819087ade3537f867ae0 completed May 3, 2026, 5:51 a.m.
NEDg Description generation batch_69f6e4c5e2888190b0bfcdf2cc25ad5f completed May 3, 2026, 6:01 a.m.
NED2 Entity disambiguation (via description) batch_69f6e5979df881909db42a735b9b1064 completed May 3, 2026, 6:05 a.m.
Created at: April 9, 2026, 9:05 p.m.