Triple

T6184757
Position Surface form Disambiguated ID Type / Status
Subject Iban language E138028 entity
Predicate hasDialect P4251 FINISHED
Object Saribas Iban
Saribas Iban is a regional dialect of the Iban language traditionally spoken by Iban communities in the Saribas area of Sarawak, Malaysia.
 E576535 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: Saribas Iban | Statement: [Iban language, hasDialect, Saribas Iban]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Saribas Iban
Context triple: [Iban language, hasDialect, Saribas Iban]
  • A. Jaku Iban
    Jaku Iban is the native name for the Iban language spoken by the Iban people of Borneo.
  • B. Dupax Isinay
    Dupax Isinay is a regional dialect of the Isinay language traditionally spoken in the Dupax area of Nueva Vizcaya in the northern Philippines.
  • C. Ilianen Manobo
    Ilianen Manobo is an Austronesian language spoken by the Ilianen Manobo people of Mindanao in the southern Philippines.
  • D. Ivasayen Ivatan
    Ivasayen Ivatan is a variety of the Ivatan language spoken by the Ivatan people of the Batanes Islands in the northern Philippines.
  • E. Kalepa Baybayan
    Kalepa Baybayan was a renowned Native Hawaiian master navigator and cultural educator known for reviving and teaching traditional Polynesian wayfinding techniques on voyaging canoes such as Hōkūleʻa.
  • 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: Saribas Iban
Triple: [Iban language, hasDialect, Saribas Iban]
Generated description
Saribas Iban is a regional dialect of the Iban language traditionally spoken by Iban communities in the Saribas area of Sarawak, Malaysia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Saribas Iban
Target entity description: Saribas Iban is a regional dialect of the Iban language traditionally spoken by Iban communities in the Saribas area of Sarawak, Malaysia.
  • A. Jaku Iban
    Jaku Iban is the native name for the Iban language spoken by the Iban people of Borneo.
  • B. Dupax Isinay
    Dupax Isinay is a regional dialect of the Isinay language traditionally spoken in the Dupax area of Nueva Vizcaya in the northern Philippines.
  • C. Ilianen Manobo
    Ilianen Manobo is an Austronesian language spoken by the Ilianen Manobo people of Mindanao in the southern Philippines.
  • D. Ivasayen Ivatan
    Ivasayen Ivatan is a variety of the Ivatan language spoken by the Ivatan people of the Batanes Islands in the northern Philippines.
  • E. Kalepa Baybayan
    Kalepa Baybayan was a renowned Native Hawaiian master navigator and cultural educator known for reviving and teaching traditional Polynesian wayfinding techniques on voyaging canoes such as Hōkūleʻa.
  • 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_69c008a8fd408190b7ec6e42934974a6 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c061020d148190ae2edf2b363f1e24 completed March 22, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c16ef823348190a8ed68141857e28c completed March 23, 2026, 4:48 p.m.
NEDg Description generation batch_69c1be0624088190b20fdfa389ebf092 completed March 23, 2026, 10:26 p.m.
NED2 Entity disambiguation (via description) batch_69c1bec4844081908baa5abbc4cb3221 completed March 23, 2026, 10:29 p.m.
Created at: March 22, 2026, 4:19 p.m.