Triple

T3858065
Position Surface form Disambiguated ID Type / Status
Subject Debub E90066 entity
Predicate hasTown P847 FINISHED
Object Segeneiti
Segeneiti is a town in southern Eritrea known for its agricultural surroundings and role as a local commercial center.
 E392883 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: Segeneiti | Statement: [Debub, hasTown, Segeneiti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Segeneiti
Context triple: [Debub, hasTown, Segeneiti]
  • A. Geno
    Geno is the widely used nickname of Hall of Fame University of Connecticut women's basketball coach Geno Auriemma.
  • B. Genn
    Genn is a surname most notably associated with British actor and barrister Leo Genn.
  • C. Geneta
    Geneta is a residential district and suburb within Södertälje Municipality in Sweden.
  • D. Agutaynen
    Agutaynen is an Austronesian language spoken by the Agutaynen people in the Philippines, primarily in the province of Palawan.
  • E. Mitanni
    Mitanni was a powerful Hurrian-speaking kingdom of the Late Bronze Age in northern Mesopotamia and Syria, known for its chariotry, diplomacy, and rivalry with contemporary great powers such as Egypt and the Hittites.
  • 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: Segeneiti
Triple: [Debub, hasTown, Segeneiti]
Generated description
Segeneiti is a town in southern Eritrea known for its agricultural surroundings and role as a local commercial center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Segeneiti
Target entity description: Segeneiti is a town in southern Eritrea known for its agricultural surroundings and role as a local commercial center.
  • A. Geno
    Geno is the widely used nickname of Hall of Fame University of Connecticut women's basketball coach Geno Auriemma.
  • B. Genn
    Genn is a surname most notably associated with British actor and barrister Leo Genn.
  • C. Geneta
    Geneta is a residential district and suburb within Södertälje Municipality in Sweden.
  • D. Agutaynen
    Agutaynen is an Austronesian language spoken by the Agutaynen people in the Philippines, primarily in the province of Palawan.
  • E. Mitanni
    Mitanni was a powerful Hurrian-speaking kingdom of the Late Bronze Age in northern Mesopotamia and Syria, known for its chariotry, diplomacy, and rivalry with contemporary great powers such as Egypt and the Hittites.
  • 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_69aed95b3c088190a8f85d19e6070599 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec1e68f88190941c39221486f6ae completed March 9, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b504228220819082e11b316ba79b08 completed March 14, 2026, 6:45 a.m.
NEDg Description generation batch_69b505420de0819086dee340f34a8886 completed March 14, 2026, 6:50 a.m.
NED2 Entity disambiguation (via description) batch_69b5064192a48190a0f95dee872437e0 completed March 14, 2026, 6:54 a.m.
Created at: March 9, 2026, 3:19 p.m.