Triple

T27527892
Position Surface form Disambiguated ID Type / Status
Subject Duong Dong E694882 entity
Predicate hasTouristAttraction P530 FINISHED
Object Dinh Cau Beach
Dinh Cau Beach is a popular seaside spot on Phu Quoc Island in Vietnam, known for its scenic sunset views and proximity to the iconic Dinh Cau Temple on a rocky promontory.
E1778649 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: Dinh Cau Beach | Statement: [Duong Dong, hasTouristAttraction, Dinh Cau Beach]
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: Dinh Cau Beach
Triple: [Duong Dong, hasTouristAttraction, Dinh Cau Beach]
Generated description
Dinh Cau Beach is a popular seaside spot on Phu Quoc Island in Vietnam, known for its scenic sunset views and proximity to the iconic Dinh Cau Temple on a rocky promontory.

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_69ef538550208190aa9de8e2cb260d93 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62f3124008190b70853a40895469e completed May 2, 2026, 5:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12d0c6f5ac81909f56e8a9a42c566b completed May 24, 2026, 10:19 a.m.
NEDg Description generation batch_6a12d169e8888190bf3c8e7f0718a3a5 completed May 24, 2026, 10:22 a.m.
NED2 Entity disambiguation (via description) batch_6a12d26af1288190a2925d726ab5be31 completed May 24, 2026, 10:26 a.m.
Created at: April 27, 2026, 1:24 p.m.