Triple

T24400569
Position Surface form Disambiguated ID Type / Status
Subject Sun Group E615153 entity
Predicate hasProject P14971 FINISHED
Object Sun World Fansipan Legend
Sun World Fansipan Legend is a large mountain resort and entertainment complex in Vietnam, known for its cable car access to Fansipan Peak and diverse tourism attractions.
E1631420 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: Sun World Fansipan Legend | Statement: [Sun Group, hasProject, Sun World Fansipan Legend]
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: Sun World Fansipan Legend
Triple: [Sun Group, hasProject, Sun World Fansipan Legend]
Generated description
Sun World Fansipan Legend is a large mountain resort and entertainment complex in Vietnam, known for its cable car access to Fansipan Peak and diverse tourism attractions.

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_69e2d7e780bc81908049c779e697a7f6 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f294da48348190bcdcab21209deaac completed April 29, 2026, 11:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fd68795b0819081bf138c848e0aa2 completed May 22, 2026, 4:07 a.m.
NEDg Description generation batch_6a0fd7f84a908190a128494e4b442ada completed May 22, 2026, 4:13 a.m.
NED2 Entity disambiguation (via description) batch_6a0fd8d0f6848190a77aff96b4fbcc3d completed May 22, 2026, 4:17 a.m.
Created at: April 18, 2026, 2:05 a.m.