Triple

T6564754
Position Surface form Disambiguated ID Type / Status
Subject Lo-Toga E153874 entity
Predicate hasDialect P4251 FINISHED
Object Lo
Lo is a dialect of the Lo-Toga language spoken on the Torres Islands in northern Vanuatu.
 E603823 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: Lo | Statement: [Lo-Toga, hasDialect, Lo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lo
Context triple: [Lo-Toga, hasDialect, Lo]
  • A. LO
    LO is Norway’s largest and most influential trade union confederation, representing a broad spectrum of workers across multiple sectors.
  • B. LO
    LO was the New York Stock Exchange ticker symbol for Lorillard Tobacco Company, a major American tobacco manufacturer best known for brands like Newport.
  • C. LO
    LO is the regional vehicle registration code assigned to the city of Vanadzor in Armenia.
  • D. Le
    Le is a common Vietnamese surname shared by many notable figures in the country’s history and culture.
  • E. Lu
    Lu is the traditional abbreviation and historical name used to refer to China’s Shandong province.
  • 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: Lo
Triple: [Lo-Toga, hasDialect, Lo]
Generated description
Lo is a dialect of the Lo-Toga language spoken on the Torres Islands in northern Vanuatu.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lo
Target entity description: Lo is a dialect of the Lo-Toga language spoken on the Torres Islands in northern Vanuatu.
  • A. LO
    LO is Norway’s largest and most influential trade union confederation, representing a broad spectrum of workers across multiple sectors.
  • B. LO
    LO was the New York Stock Exchange ticker symbol for Lorillard Tobacco Company, a major American tobacco manufacturer best known for brands like Newport.
  • C. LO
    LO is the regional vehicle registration code assigned to the city of Vanadzor in Armenia.
  • D. Le
    Le is a common Vietnamese surname shared by many notable figures in the country’s history and culture.
  • E. Lu
    Lu is the traditional abbreviation and historical name used to refer to China’s Shandong province.
  • 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_69c6880cb35881909b763eb0125236b9 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ae3b9ec8819080f3052556d95810 completed March 27, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d5622e0481909b0ac0f4e06d19bc completed March 27, 2026, 7:07 p.m.
NEDg Description generation batch_69c6d828620081909c1b4dfaa96efd62 completed March 27, 2026, 7:19 p.m.
NED2 Entity disambiguation (via description) batch_69c6d8a3d194819080f33e179a8a8679 completed March 27, 2026, 7:21 p.m.
Created at: March 27, 2026, 1:52 p.m.