Triple

T30659260
Position Surface form Disambiguated ID Type / Status
Subject Binh Phuoc Province E780477 entity
Predicate hasAdministrativeUnit P3892 FINISHED
Object Chon Thanh District
Chon Thanh District is a rural administrative district located in southern Vietnam’s Bình Phước Province, known for its agriculture and growing industrial development.
E2062132 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: Chon Thanh District | Statement: [Binh Phuoc Province, hasAdministrativeUnit, Chon Thanh District]
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: Chon Thanh District
Triple: [Binh Phuoc Province, hasAdministrativeUnit, Chon Thanh District]
Generated description
Chon Thanh District is a rural administrative district located in southern Vietnam’s Bình Phước Province, known for its agriculture and growing industrial development.

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_69f224a6d10481909290be1a00fc83b3 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68adf0f908190aba108c90a766428 completed May 2, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3626f8659c8190880f1474bd96f51b completed June 20, 2026, 5:36 a.m.
NEDg Description generation batch_6a36279033e081909b97ac755ae90116 completed June 20, 2026, 5:39 a.m.
NED2 Entity disambiguation (via description) batch_6a362968a6c08190beb1123ec9f3b337 completed June 20, 2026, 5:47 a.m.
Created at: April 29, 2026, 8:30 p.m.