Triple

T34575705
Position Surface form Disambiguated ID Type / Status
Subject Capitol Singapore E887745 entity
Predicate hasPart P35 FINISHED
Object Arcade at The Capitol Kempinski
Arcade at The Capitol Kempinski is a luxury lifestyle and retail wing of the Capitol Kempinski complex in Singapore, featuring upscale boutiques, dining venues, and services in a heritage setting.
E2103056 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: Arcade at The Capitol Kempinski | Statement: [Capitol Singapore, hasPart, Arcade at The Capitol Kempinski]
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: Arcade at The Capitol Kempinski
Triple: [Capitol Singapore, hasPart, Arcade at The Capitol Kempinski]
Generated description
Arcade at The Capitol Kempinski is a luxury lifestyle and retail wing of the Capitol Kempinski complex in Singapore, featuring upscale boutiques, dining venues, and services in a heritage setting.

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_69f349d1a5fc81908557a46875b2f157 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f720999db48190b89014e3ec01cb62 completed May 3, 2026, 10:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3736323418819092ec4ee55ea9a991 completed June 21, 2026, 12:54 a.m.
NEDg Description generation batch_6a37372aa9608190a607c9b4d0c4f978 completed June 21, 2026, 12:58 a.m.
NED2 Entity disambiguation (via description) batch_6a373a7631588190a8fb371e7e7338ac completed June 21, 2026, 1:12 a.m.
Created at: May 1, 2026, 2:03 a.m.