Triple

T6564980
Position Surface form Disambiguated ID Type / Status
Subject Sakao E153880 entity
Predicate hasAlternativeName P39 FINISHED
Object Sakao language
The Sakao language is an Oceanic language spoken on Espiritu Santo Island in Vanuatu, known for its complex phonology and rich system of verbal morphology.
 E603846 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: Sakao language | Statement: [Sakao, hasAlternativeName, Sakao language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sakao language
Context triple: [Sakao, hasAlternativeName, Sakao language]
  • A. Sakizaya language
    The Sakizaya language is an indigenous Austronesian language spoken by the Sakizaya people of eastern Taiwan.
  • B. Saho language
    The Saho language is an Afroasiatic Cushitic language spoken primarily by the Saho people in Eritrea and northern Ethiopia.
  • C. Akawaio language
    The Akawaio language is an indigenous Cariban language spoken by the Akawaio people of Guyana, Venezuela, and Brazil.
  • D. Segai language
    The Segai language is an Austronesian language spoken by the Segai people of Borneo, belonging to the Kayanic subgroup.
  • E. Mikasuki language
    The Mikasuki language is a Native American Muskogean language traditionally spoken by the Miccosukee and Seminole peoples of Florida.
  • 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: Sakao language
Triple: [Sakao, hasAlternativeName, Sakao language]
Generated description
The Sakao language is an Oceanic language spoken on Espiritu Santo Island in Vanuatu, known for its complex phonology and rich system of verbal morphology.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sakao language
Target entity description: The Sakao language is an Oceanic language spoken on Espiritu Santo Island in Vanuatu, known for its complex phonology and rich system of verbal morphology.
  • A. Sakizaya language
    The Sakizaya language is an indigenous Austronesian language spoken by the Sakizaya people of eastern Taiwan.
  • B. Saho language
    The Saho language is an Afroasiatic Cushitic language spoken primarily by the Saho people in Eritrea and northern Ethiopia.
  • C. Akawaio language
    The Akawaio language is an indigenous Cariban language spoken by the Akawaio people of Guyana, Venezuela, and Brazil.
  • D. Segai language
    The Segai language is an Austronesian language spoken by the Segai people of Borneo, belonging to the Kayanic subgroup.
  • E. Mikasuki language
    The Mikasuki language is a Native American Muskogean language traditionally spoken by the Miccosukee and Seminole peoples of Florida.
  • 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.