Triple

T32824910
Position Surface form Disambiguated ID Type / Status
Subject Kandangan E839530 entity
Predicate culturalRegion P1968 FINISHED
Object Banjar cultural area
The Banjar cultural area is a region in South Kalimantan, Indonesia, characterized by the traditions, language, and Islamic-influenced customs of the Banjar ethnic group.
E2024287 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: Banjar cultural area | Statement: [Kandangan, culturalRegion, Banjar cultural area]
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: Banjar cultural area
Triple: [Kandangan, culturalRegion, Banjar cultural area]
Generated description
The Banjar cultural area is a region in South Kalimantan, Indonesia, characterized by the traditions, language, and Islamic-influenced customs of the Banjar ethnic group.

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_69f3493f22f88190ae6dd4bc15b6cf8d completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6cdf546a081908b0ca5d773804402 completed May 3, 2026, 4:24 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34b1854b9c8190963e9f13eabeec68 completed June 19, 2026, 3:03 a.m.
NEDg Description generation batch_6a34b28809fc819090b804d470dba1b3 completed June 19, 2026, 3:07 a.m.
NED2 Entity disambiguation (via description) batch_6a34b3356258819086890e71c40d1f9b completed June 19, 2026, 3:10 a.m.
Created at: May 1, 2026, 1:15 a.m.