Triple

T19790650
Position Surface form Disambiguated ID Type / Status
Subject Temeke E475399 entity
Predicate contains P35 FINISHED
Object Mtoni
Mtoni is a residential ward and neighborhood within the Temeke District of Dar es Salaam, Tanzania.
E1395220 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: Mtoni | Statement: [Temeke, contains, Mtoni]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mtoni
Context triple: [Temeke, contains, Mtoni]
  • A. Manyoni
    Manyoni is a town and district headquarters in central Tanzania known for its location along major road and rail routes in the Singida Region.
  • B. Mukuzani
    Mukuzani is a renowned Georgian red wine appellation known for producing dry, oak-aged wines from the Saperavi grape in the Kakheti region.
  • C. Mkushi
    Mkushi is a farming and trading town in Zambia known for its commercial agriculture, particularly large-scale commercial farming.
  • D. Musanga
    Musanga is a small genus of fast-growing tropical African trees in the nettle family, best known for the umbrella tree (Musanga cecropioides) commonly found in rainforest and disturbed habitats.
  • E. Mlolongo
    Mlolongo is a rapidly growing urban town in Kenya’s Machakos County, situated along the Nairobi–Mombasa highway and known for its bustling commercial activity and residential estates.
  • 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: Mtoni
Triple: [Temeke, contains, Mtoni]
Generated description
Mtoni is a residential ward and neighborhood within the Temeke District of Dar es Salaam, Tanzania.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mtoni
Target entity description: Mtoni is a residential ward and neighborhood within the Temeke District of Dar es Salaam, Tanzania.
  • A. Manyoni
    Manyoni is a town and district headquarters in central Tanzania known for its location along major road and rail routes in the Singida Region.
  • B. Mukuzani
    Mukuzani is a renowned Georgian red wine appellation known for producing dry, oak-aged wines from the Saperavi grape in the Kakheti region.
  • C. Mkushi
    Mkushi is a farming and trading town in Zambia known for its commercial agriculture, particularly large-scale commercial farming.
  • D. Musanga
    Musanga is a small genus of fast-growing tropical African trees in the nettle family, best known for the umbrella tree (Musanga cecropioides) commonly found in rainforest and disturbed habitats.
  • E. Mlolongo
    Mlolongo is a rapidly growing urban town in Kenya’s Machakos County, situated along the Nairobi–Mombasa highway and known for its bustling commercial activity and residential estates.
  • 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_69d8e51b014081908b263e167370529a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e653c217bc819092c517b27ca22087 completed April 20, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07c4fff3548190a069b665c0885627 completed May 16, 2026, 1:14 a.m.
NEDg Description generation batch_6a07c580b3108190bcc64fe1f479d7c4 completed May 16, 2026, 1:16 a.m.
NED2 Entity disambiguation (via description) batch_6a07c5e7a5d08190b6a24f66ff966cec completed May 16, 2026, 1:18 a.m.
Created at: April 10, 2026, 1:49 p.m.