Triple

T23094166
Position Surface form Disambiguated ID Type / Status
Subject Mara language E575837 entity
Predicate hasAlternativeName P39 FINISHED
Object Lakher language
Lakher language is a Kuki-Chin language of the Tibeto-Burman family spoken primarily by the Mara people in northeastern India and neighboring Myanmar.
 E1570424 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: Lakher language | Statement: [Mara language, hasAlternativeName, Lakher language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lakher language
Context triple: [Mara language, hasAlternativeName, Lakher language]
  • A. Lak language
    The Lak language is a Northeast Caucasian language spoken primarily by the Lak people in the Republic of Dagestan in the North Caucasus region of Russia.
  • B. Lakalai language
    The Lakalai language is an Austronesian language spoken by the Lakalai people of New Britain in Papua New Guinea.
  • C. Laha language
    The Laha language is a lesser-known Kra language spoken by the Laha ethnic group in northern Vietnam.
  • D. Laka language
    Laka language is a lesser-known Adamawa–Ubangi language spoken in parts of Central Africa, particularly in Chad and neighboring regions.
  • E. Belhare language
    The Belhare language is a Kiranti language of the Sino-Tibetan family spoken by the Belhare community in eastern Nepal.
  • 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: Lakher language
Triple: [Mara language, hasAlternativeName, Lakher language]
Generated description
Lakher language is a Kuki-Chin language of the Tibeto-Burman family spoken primarily by the Mara people in northeastern India and neighboring Myanmar.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lakher language
Target entity description: Lakher language is a Kuki-Chin language of the Tibeto-Burman family spoken primarily by the Mara people in northeastern India and neighboring Myanmar.
  • A. Lak language
    The Lak language is a Northeast Caucasian language spoken primarily by the Lak people in the Republic of Dagestan in the North Caucasus region of Russia.
  • B. Lakalai language
    The Lakalai language is an Austronesian language spoken by the Lakalai people of New Britain in Papua New Guinea.
  • C. Laha language
    The Laha language is a lesser-known Kra language spoken by the Laha ethnic group in northern Vietnam.
  • D. Laka language
    Laka language is a lesser-known Adamawa–Ubangi language spoken in parts of Central Africa, particularly in Chad and neighboring regions.
  • E. Belhare language
    The Belhare language is a Kiranti language of the Sino-Tibetan family spoken by the Belhare community in eastern Nepal.
  • 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_69e245c060b48190a9bd61a47a16db17 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18de2ed088190971ff08c58b15aad completed April 29, 2026, 4:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c15b97b6881909cbc1afc68ea80b6 completed May 19, 2026, 7:48 a.m.
NEDg Description generation batch_6a0c175e246081909d6451f245ccfe66 completed May 19, 2026, 7:55 a.m.
NED2 Entity disambiguation (via description) batch_6a0c1820a4d88190aed59f50b4e7ec47 completed May 19, 2026, 7:58 a.m.
Created at: April 17, 2026, 3:57 p.m.