Triple

T5970984
Position Surface form Disambiguated ID Type / Status
Subject Iban people E132870 entity
Predicate language P15 FINISHED
Object Iban language E138028 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: Iban language | Statement: [Iban people, language, Iban language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Iban language
Context triple: [Iban people, language, Iban language]
  • A. Iban language chosen
    The Iban language is an Austronesian language spoken primarily by the Iban people of Borneo, especially in Sarawak, Malaysia, and parts of Kalimantan, Indonesia.
  • B. Banjar language
    The Banjar language is an Austronesian language spoken primarily by the Banjar people of South Kalimantan, Indonesia, and is considered a regional variety closely associated with the broader Malay linguistic family.
  • C. Sabine language
    The Sabine language was an extinct Italic tongue once spoken by the ancient Sabine people of central Italy, closely related to other Osco-Umbrian languages.
  • D. Ibanag language
    The Ibanag language is an Austronesian language spoken primarily in the Cagayan Valley region of northern Luzon in the Philippines.
  • E. Baniwa language
    Baniwa is an Arawakan Indigenous language spoken primarily along the Rio Negro in northwestern Brazil, as well as in parts of Colombia and Venezuela.
  • 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_69c0086deab081908550159ca23eec9b completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c03a7fd1ec8190926927b7c3cbec0a completed March 22, 2026, 6:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e40a67bc8190a57884f7c6aa1b9d completed March 23, 2026, 6:56 a.m.
Created at: March 22, 2026, 4:03 p.m.