Triple

T23061034
Position Surface form Disambiguated ID Type / Status
Subject Jaku Iban E574300 entity
Predicate hasDialect P4251 FINISHED
Object Ulu Ai dialect
The Ulu Ai dialect is a regional variety of the Iban language spoken by Iban communities living in the upriver (interior) areas of Borneo.
 E1567658 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: Ulu Ai dialect | Statement: [Jaku Iban, hasDialect, Ulu Ai dialect]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ulu Ai dialect
Context triple: [Jaku Iban, hasDialect, Ulu Ai dialect]
  • A. Taai dialect
    The Taai dialect is a regional variety of the Saisiyat language spoken by the indigenous Saisiyat people of Taiwan.
  • B. Belui dialect
    The Belui dialect is a regional variety of the Kerinci language spoken by communities in parts of Sumatra, Indonesia.
  • C. Nohurli dialect
    The Nohurli dialect is a regional variety of Turkmen spoken by the Nohur people in parts of Turkmenistan, distinguished by its unique phonetic and lexical features.
  • D. Tappalang dialect
    The Tappalang dialect is a regional variety of the Mandar language spoken by Mandar communities in parts of West Sulawesi, Indonesia.
  • E. Kikai dialect
    The Kikai dialect is a regional variety of the Amami language spoken on Kikai Island in Japan’s Ryukyu archipelago.
  • 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: Ulu Ai dialect
Triple: [Jaku Iban, hasDialect, Ulu Ai dialect]
Generated description
The Ulu Ai dialect is a regional variety of the Iban language spoken by Iban communities living in the upriver (interior) areas of Borneo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ulu Ai dialect
Target entity description: The Ulu Ai dialect is a regional variety of the Iban language spoken by Iban communities living in the upriver (interior) areas of Borneo.
  • A. Taai dialect
    The Taai dialect is a regional variety of the Saisiyat language spoken by the indigenous Saisiyat people of Taiwan.
  • B. Belui dialect
    The Belui dialect is a regional variety of the Kerinci language spoken by communities in parts of Sumatra, Indonesia.
  • C. Nohurli dialect
    The Nohurli dialect is a regional variety of Turkmen spoken by the Nohur people in parts of Turkmenistan, distinguished by its unique phonetic and lexical features.
  • D. Tappalang dialect
    The Tappalang dialect is a regional variety of the Mandar language spoken by Mandar communities in parts of West Sulawesi, Indonesia.
  • E. Kikai dialect
    The Kikai dialect is a regional variety of the Amami language spoken on Kikai Island in Japan’s Ryukyu archipelago.
  • 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_69e245ba7ae48190be606dbc54120e39 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1899ff96081908d89a07a3b1065c8 completed April 29, 2026, 4:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c0ae626788190b55ab452779b32c8 completed May 19, 2026, 7:01 a.m.
NEDg Description generation batch_6a0c0bfdc59481908f7d25160e7cf46d completed May 19, 2026, 7:06 a.m.
NED2 Entity disambiguation (via description) batch_6a0c0c7c5bb081909bcd6d2d2571f0cb completed May 19, 2026, 7:08 a.m.
Created at: April 17, 2026, 3:55 p.m.