Triple

T7291039
Position Surface form Disambiguated ID Type / Status
Subject Blablanga language E164391 entity
Predicate neighboringLanguage P16383 FINISHED
Object Zabana language E147715 NE FINISHED

How this triple was built (2 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: Zabana language | Statement: [Blablanga language, neighboringLanguage, Zabana language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zabana language
Context triple: [Blablanga language, neighboringLanguage, Zabana language]
  • A. Zabana language chosen
    The Zabana language is an Oceanic language spoken primarily on Santa Isabel Island in the Solomon Islands.
  • B. Zhaba language
    The Zhaba language is a lesser-known Qiangic tongue spoken by the Zhaba people in parts of Sichuan, China, and is considered endangered.
  • C. Zay language
    Zay language is a South Ethiopic Semitic language spoken by the Zay people on islands and shores of Lake Zway in Ethiopia.
  • D. Zambal language
    Zambal language is an Austronesian language spoken by the Sambal people primarily in the Zambales region of the Philippines.
  • E. Zaiwa language
    The Zaiwa language is a Tibeto-Burman language spoken primarily by the Zaiwa people in parts of Yunnan, China and northern Myanmar.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c6887a499881909dd23341399c59d8 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6eb6e8f3881908628b3d41aad70c6 completed March 27, 2026, 8:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7db4a31608190ba465e22e7a81782 completed March 28, 2026, 1:44 p.m.
Created at: March 27, 2026, 3 p.m.