Triple

T36378932
Position Surface form Disambiguated ID Type / Status
Subject Ba Ria–Vung Tau Province E895987 entity
Predicate contains P35 FINISHED
Object Tan Thanh area
Tan Thanh area is a coastal industrial and urban zone within Bà Rịa–Vũng Tàu Province in southern Vietnam, known for its ports, manufacturing, and proximity to key economic corridors.
 E2181962 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: Tan Thanh area | Statement: [Ba Ria–Vung Tau Province, contains, Tan Thanh 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: Tan Thanh area
Triple: [Ba Ria–Vung Tau Province, contains, Tan Thanh area]
Generated description
Tan Thanh area is a coastal industrial and urban zone within Bà Rịa–Vũng Tàu Province in southern Vietnam, known for its ports, manufacturing, and proximity to key economic corridors.

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_69f76e51d358819092bbc5f119f49476 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bb191af8819085752b8046efc840 completed May 3, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39b42e34d881908519daa5c854436b completed June 22, 2026, 10:16 p.m.
NEDg Description generation batch_6a39b69746d88190b74cd108c74aa54f completed June 22, 2026, 10:26 p.m.
NED2 Entity disambiguation (via description) batch_6a39b7796e1c81909600a1b006e33ac8 completed June 22, 2026, 10:30 p.m.
Created at: May 3, 2026, 4:10 p.m.