Triple

T6786758
Position Surface form Disambiguated ID Type / Status
Subject Bel languages E155826 entity
Predicate hasMember P10 FINISHED
Object Wab language
The Wab language is a lesser-known Papuan language spoken by an indigenous community in Papua New Guinea.
 E619320 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: Wab language | Statement: [Bel languages, hasMember, Wab language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Wab language
Context triple: [Bel languages, hasMember, Wab language]
  • A. Wapishana language
    The Wapishana language is an indigenous Arawakan language spoken primarily by the Wapishana people in parts of Brazil and Guyana.
  • B. Waja language
    The Waja language is a lesser-known Niger-Congo language spoken by the Waja people of northeastern Nigeria.
  • C. Wa language
    The Wa language is a Mon–Khmer language spoken primarily by the Wa people in parts of Myanmar and China.
  • D. Wawonii language
    The Wawonii language is an Austronesian language spoken on Wawonii Island in Southeast Sulawesi, Indonesia, and is part of the Bungku–Tolaki language group.
  • E. Wetar language
    The Wetar language is an Austronesian language spoken on Wetar Island in Indonesia’s Maluku province, known for its distinct phonology and role in the Timor–Babar subgroup.
  • 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: Wab language
Triple: [Bel languages, hasMember, Wab language]
Generated description
The Wab language is a lesser-known Papuan language spoken by an indigenous community in Papua New Guinea.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Wab language
Target entity description: The Wab language is a lesser-known Papuan language spoken by an indigenous community in Papua New Guinea.
  • A. Wapishana language
    The Wapishana language is an indigenous Arawakan language spoken primarily by the Wapishana people in parts of Brazil and Guyana.
  • B. Waja language
    The Waja language is a lesser-known Niger-Congo language spoken by the Waja people of northeastern Nigeria.
  • C. Wa language
    The Wa language is a Mon–Khmer language spoken primarily by the Wa people in parts of Myanmar and China.
  • D. Wawonii language
    The Wawonii language is an Austronesian language spoken on Wawonii Island in Southeast Sulawesi, Indonesia, and is part of the Bungku–Tolaki language group.
  • E. Wetar language
    The Wetar language is an Austronesian language spoken on Wetar Island in Indonesia’s Maluku province, known for its distinct phonology and role in the Timor–Babar subgroup.
  • 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_69c6881770fc8190972b2906390380f5 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d28f043081909a9a9ab635785933 completed March 27, 2026, 6:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71a871a84819098891f66c6e5b579 completed March 28, 2026, 12:02 a.m.
NEDg Description generation batch_69c71b6b87d8819085e6ae122f042626 completed March 28, 2026, 12:06 a.m.
NED2 Entity disambiguation (via description) batch_69c71c00f86c819099ef6ae0766e9f3a completed March 28, 2026, 12:08 a.m.
Created at: March 27, 2026, 2:14 p.m.