Triple

T19732925
Position Surface form Disambiguated ID Type / Status
Subject Quảng Điền District E473898 entity
Predicate traversedBy P225 FINISHED
Object Bồ River
Bồ River is a river in central Vietnam that flows through Thừa Thiên Huế province, contributing to local agriculture, transportation, and flood dynamics before joining the Perfume River system.
E1592493 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: Bồ River | Statement: [Quảng Điền District, traversedBy, Bồ River]
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: Bồ River
Triple: [Quảng Điền District, traversedBy, Bồ River]
Generated description
Bồ River is a river in central Vietnam that flows through Thừa Thiên Huế province, contributing to local agriculture, transportation, and flood dynamics before joining the Perfume River system.

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_69d8e517ebd48190979ee76723bcfadf completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e651596b98819090bcaf05c7b74555 completed April 20, 2026, 4:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0f4531481c81908b3c1e81d1322994 completed May 21, 2026, 5:47 p.m.
NEDg Description generation batch_6a0f46b69d288190b3fb6dcea9fb44b5 completed May 21, 2026, 5:53 p.m.
NED2 Entity disambiguation (via description) batch_6a0f476e8eb88190a895453552c92b9a completed May 21, 2026, 5:57 p.m.
Created at: April 10, 2026, 1:47 p.m.