Triple

T30478565
Position Surface form Disambiguated ID Type / Status
Subject Kasong E775510 entity
Predicate relatedTo P37 FINISHED
Object Chong language
The Chong language is an endangered Austroasiatic language spoken by small communities in eastern Thailand and western Cambodia, notable for preserving archaic features of the Pearic branch.
E805416 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: Chong language | Statement: [Kasong, relatedTo, Chong 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: Chong language
Triple: [Kasong, relatedTo, Chong language]
Generated description
The Chong language is an endangered Austroasiatic language spoken by small communities in eastern Thailand and western Cambodia, notable for preserving archaic features of the Pearic branch.

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_69f22497341481909c21ba329fadaa6b completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6871ae044819096fece430cc1f9f9 completed May 2, 2026, 11:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2856e777448190beaeb69b0cce341b completed June 9, 2026, 6:09 p.m.
NEDg Description generation batch_6a28576e33808190a5ccbb4f0e7eb431 completed June 9, 2026, 6:11 p.m.
NED2 Entity disambiguation (via description) batch_6a2857fab72c8190a89b5ec5ced6aa17 completed June 9, 2026, 6:14 p.m.
Created at: April 29, 2026, 8:12 p.m.