Triple

T13436024
Position Surface form Disambiguated ID Type / Status
Subject Genoese dialect E320230 entity
Predicate hasAlternativeName P39 FINISHED
Object Zeneize
Zeneize is the traditional Ligurian language variety spoken in and around the Italian city of Genoa.
E1041694 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: Zeneize | Statement: [Genoese dialect, hasAlternativeName, Zeneize]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zeneize
Context triple: [Genoese dialect, hasAlternativeName, Zeneize]
  • A. Ninzam
    Ninzam is a Plateau language of central Nigeria, spoken by a small ethnic community and known for its place within the Benue–Congo branch of the Niger-Congo language family.
  • B. Tunechi
    Tunechi is a popular nickname and alter ego of American rapper Lil Wayne, often used to refer to his distinctive persona and musical brand.
  • C. Zuiker
    Zuiker is the surname of Anthony E. Zuiker, the American television writer and producer best known as the creator of the CSI franchise.
  • D. Takkaze
    Takkaze is a river in northern Ethiopia that flows through deep gorges before joining the Atbarah River, ultimately contributing to the Nile basin.
  • E. Zeen
    Zeen was a web-based publishing tool that allowed users to easily create and share digital magazines and visual stories online.
  • 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: Zeneize
Triple: [Genoese dialect, hasAlternativeName, Zeneize]
Generated description
Zeneize is the traditional Ligurian language variety spoken in and around the Italian city of Genoa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Zeneize
Target entity description: Zeneize is the traditional Ligurian language variety spoken in and around the Italian city of Genoa.
  • A. Ninzam
    Ninzam is a Plateau language of central Nigeria, spoken by a small ethnic community and known for its place within the Benue–Congo branch of the Niger-Congo language family.
  • B. Tunechi
    Tunechi is a popular nickname and alter ego of American rapper Lil Wayne, often used to refer to his distinctive persona and musical brand.
  • C. Zuiker
    Zuiker is the surname of Anthony E. Zuiker, the American television writer and producer best known as the creator of the CSI franchise.
  • D. Takkaze
    Takkaze is a river in northern Ethiopia that flows through deep gorges before joining the Atbarah River, ultimately contributing to the Nile basin.
  • E. Zeen
    Zeen was a web-based publishing tool that allowed users to easily create and share digital magazines and visual stories online.
  • 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_69d80761e6cc8190a90c844589998ecc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaee42a8c8190a85716b4a6db335e completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f739902d148190ac14ac66f1f9512f completed May 3, 2026, 12:03 p.m.
NEDg Description generation batch_69f73d6051e48190a39e8de98bfb839a completed May 3, 2026, 12:19 p.m.
NED2 Entity disambiguation (via description) batch_69f7411fbb9481908f0106b01f2583bf completed May 3, 2026, 12:35 p.m.
Created at: April 9, 2026, 9:40 p.m.