Triple

T10956884
Position Surface form Disambiguated ID Type / Status
Subject Arusha Region E258867 entity
Predicate containsTown P847 FINISHED
Object Longido
Longido is a town in northern Tanzania that serves as a local center near Mount Longido and the Kenyan border within the Arusha Region.
E897781 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: Longido | Statement: [Arusha Region, containsTown, Longido]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Longido
Context triple: [Arusha Region, containsTown, Longido]
  • A. Longiano
    Longiano is a historic hilltop town in Italy’s Emilia-Romagna region, known for its medieval castle, scenic views, and well-preserved old center.
  • B. Eliada
    Eliada is a lesser-known biblical figure mentioned in the Old Testament as one of King David’s sons.
  • C. Calagurris
    Calagurris was an ancient Roman town in Hispania Tarraconensis, located in what is now northern Spain and known as the birthplace of the rhetorician Quintilian.
  • D. Gisondo
    Gisondo is an Italian-origin surname most notably borne by American actor Skyler Gisondo.
  • E. Dainzú
    Dainzú is an ancient Zapotec archaeological site in Oaxaca, Mexico, notable for its terraced architecture and carved stone reliefs depicting ballgame scenes.
  • 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: Longido
Triple: [Arusha Region, containsTown, Longido]
Generated description
Longido is a town in northern Tanzania that serves as a local center near Mount Longido and the Kenyan border within the Arusha Region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Longido
Target entity description: Longido is a town in northern Tanzania that serves as a local center near Mount Longido and the Kenyan border within the Arusha Region.
  • A. Longiano
    Longiano is a historic hilltop town in Italy’s Emilia-Romagna region, known for its medieval castle, scenic views, and well-preserved old center.
  • B. Eliada
    Eliada is a lesser-known biblical figure mentioned in the Old Testament as one of King David’s sons.
  • C. Calagurris
    Calagurris was an ancient Roman town in Hispania Tarraconensis, located in what is now northern Spain and known as the birthplace of the rhetorician Quintilian.
  • D. Gisondo
    Gisondo is an Italian-origin surname most notably borne by American actor Skyler Gisondo.
  • E. Dainzú
    Dainzú is an ancient Zapotec archaeological site in Oaxaca, Mexico, notable for its terraced architecture and carved stone reliefs depicting ballgame scenes.
  • 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_69d6aa88500c819097d7032ca578e74f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d771260e9881909401a7a7466e1b8a completed April 9, 2026, 9:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3447d8cc88190a3e28f204a93a7d3 completed April 18, 2026, 8:44 a.m.
NEDg Description generation batch_69e3556ad7ec819095b3babc67ecdfd4 completed April 18, 2026, 9:56 a.m.
NED2 Entity disambiguation (via description) batch_69e358f860f08190bfd10519ff3806aa completed April 18, 2026, 10:12 a.m.
Created at: April 8, 2026, 9:23 p.m.