Triple

T11515999
Position Surface form Disambiguated ID Type / Status
Subject Iraqw E273031 entity
Predicate closelyRelatedTo P37 FINISHED
Object Alagwa language
The Alagwa language is a South Cushitic language spoken by the Alagwa people of north-central Tanzania.
 E930676 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: Alagwa language | Statement: [Iraqw, closelyRelatedTo, Alagwa language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Alagwa language
Context triple: [Iraqw, closelyRelatedTo, Alagwa language]
  • A. Agutaynen language
    Agutaynen is an Austronesian language spoken by the Agutaynen people of Palawan in the Philippines.
  • B. Lagwan language
    The Lagwan language is a Chadic language spoken by the Kotoko people of the Lake Chad region in Cameroon and Chad.
  • C. Tawala language
    Tawala language is an Austronesian language of the Papuan Tip region of Papua New Guinea, spoken primarily in coastal communities of Milne Bay Province.
  • D. Agul language
    The Agul language is a Northeast Caucasian language spoken primarily by the Agul people in southern Dagestan, Russia, known for its complex phonology and rich system of noun cases.
  • E. Kalanguya language
    The Kalanguya language is an Austronesian language spoken by the Kalanguya people in the northern Luzon highlands of the Philippines.
  • 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: Alagwa language
Triple: [Iraqw, closelyRelatedTo, Alagwa language]
Generated description
The Alagwa language is a South Cushitic language spoken by the Alagwa people of north-central Tanzania.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Alagwa language
Target entity description: The Alagwa language is a South Cushitic language spoken by the Alagwa people of north-central Tanzania.
  • A. Agutaynen language
    Agutaynen is an Austronesian language spoken by the Agutaynen people of Palawan in the Philippines.
  • B. Lagwan language
    The Lagwan language is a Chadic language spoken by the Kotoko people of the Lake Chad region in Cameroon and Chad.
  • C. Tawala language
    Tawala language is an Austronesian language of the Papuan Tip region of Papua New Guinea, spoken primarily in coastal communities of Milne Bay Province.
  • D. Agul language
    The Agul language is a Northeast Caucasian language spoken primarily by the Agul people in southern Dagestan, Russia, known for its complex phonology and rich system of noun cases.
  • E. Kalanguya language
    The Kalanguya language is an Austronesian language spoken by the Kalanguya people in the northern Luzon highlands of the Philippines.
  • 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_69d6aae2c3748190bed2ea50dfb160dc completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d87fcc72a48190b81acedfcc8685d3 completed April 10, 2026, 4:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69e625143a608190a1119b30c08df0fd completed April 20, 2026, 1:07 p.m.
NEDg Description generation batch_69e62cf44018819094818f11ac653763 completed April 20, 2026, 1:41 p.m.
NED2 Entity disambiguation (via description) batch_69e674c3a98c8190b32dc6879cb3a5f9 completed April 20, 2026, 6:47 p.m.
Created at: April 8, 2026, 9:36 p.m.