Triple

T30372317
Position Surface form Disambiguated ID Type / Status
Subject Chungli dialect E772583 entity
Predicate subdivisionOf P258 FINISHED
Object Ao Naga language
Ao Naga language is a Sino-Tibetan language spoken primarily by the Ao Naga people of Nagaland in northeastern India, encompassing several dialects including Chungli.
E1920208 NE FINISHED

How this triple was built (2 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: Ao Naga language | Statement: [Chungli dialect, subdivisionOf, Ao Naga language]
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: Ao Naga language
Triple: [Chungli dialect, subdivisionOf, Ao Naga language]
Generated description
Ao Naga language is a Sino-Tibetan language spoken primarily by the Ao Naga people of Nagaland in northeastern India, encompassing several dialects including Chungli.

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_69f2248d71408190aec0d5c2001b1cff completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6828532d081909897bbe49b280ced completed May 2, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27be580dc08190a815c1029541ebd6 completed June 9, 2026, 7:18 a.m.
NEDg Description generation batch_6a27c344fc7c8190b0be71c6332a7736 completed June 9, 2026, 7:39 a.m.
NED2 Entity disambiguation (via description) batch_6a27c3dd7c408190a9040112fd8127e9 completed June 9, 2026, 7:42 a.m.
Created at: April 29, 2026, 7:59 p.m.