Triple

T74734
Position Surface form Disambiguated ID Type / Status
Subject Libya E1495 entity
Predicate recognizedLanguage P238 FINISHED
Object Tebu
Tebu is a Saharan ethnic group and language community primarily inhabiting parts of southern Libya, Chad, and Niger.
E6206 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: Tebu | Statement: [Libya, recognizedLanguage, Tebu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tebu
Context triple: [Libya, recognizedLanguage, Tebu]
  • A. Culebra
    Culebra is a small Caribbean island municipality of Puerto Rico known for its pristine beaches, clear waters, and protected wildlife refuges.
  • B. Lick
    Lick is the nickname of Joseph Carl Robnett Licklider, a pioneering American computer scientist whose ideas helped lay the foundations for interactive computing and the internet.
  • C. Gori
    Gori is a city in central Georgia best known as the birthplace of Soviet leader Joseph Stalin.
  • D. Mango
    Mango is a sweet, tropical stone fruit widely cultivated and consumed around the world, especially in South Asia.
  • E. Boric
    Boric is the surname of Gabriel Boric, the Chilean politician who became one of the world’s youngest heads of state when he was elected President of Chile.
  • 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: Tebu
Triple: [Libya, recognizedLanguage, Tebu]
Generated description
Tebu is a Saharan ethnic group and language community primarily inhabiting parts of southern Libya, Chad, and Niger.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tebu
Target entity description: Tebu is a Saharan ethnic group and language community primarily inhabiting parts of southern Libya, Chad, and Niger.
  • A. Culebra
    Culebra is a small Caribbean island municipality of Puerto Rico known for its pristine beaches, clear waters, and protected wildlife refuges.
  • B. Namba
    Namba is a major commercial and entertainment district in Osaka, Japan, known for its bustling nightlife, shopping, and iconic neon-lit streets.
  • C. Mouton
    Mouton is an academic publishing house known for its influential works in linguistics and related fields.
  • D. Koba
    Koba was a revolutionary alias used by Joseph Stalin during his early political activities in the Bolshevik movement.
  • E. Lick
    Lick is the nickname of Joseph Carl Robnett Licklider, a pioneering American computer scientist whose ideas helped lay the foundations for interactive computing and the internet.
  • 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_69a24c60d19c8190a1b6c105ca59ef5b completed Feb. 28, 2026, 2:01 a.m.
NER Named-entity recognition batch_69a24f1b99a48190aec004ecd49b4a0d completed Feb. 28, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2554ffb8c8190a30aceecd7f30d96 completed Feb. 28, 2026, 2:39 a.m.
NEDg Description generation batch_69a25943cba88190a78f708d453ce968 completed Feb. 28, 2026, 2:56 a.m.
NED2 Entity disambiguation (via description) batch_69a259c2706c8190b5319c004e207c29 completed Feb. 28, 2026, 2:58 a.m.
Created at: Feb. 28, 2026, 2:06 a.m.