Triple

T31687979
Position Surface form Disambiguated ID Type / Status
Subject Arau, Perlis E808711 entity
Predicate hasPlaceOfWorship P1191 FINISHED
Object State Mosque of Perlis
The State Mosque of Perlis is the main state mosque and a prominent Islamic religious and architectural landmark located in Arau, the royal capital of Perlis, Malaysia.
E1974690 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: State Mosque of Perlis | Statement: [Arau, Perlis, hasPlaceOfWorship, State Mosque of Perlis]
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: State Mosque of Perlis
Triple: [Arau, Perlis, hasPlaceOfWorship, State Mosque of Perlis]
Generated description
The State Mosque of Perlis is the main state mosque and a prominent Islamic religious and architectural landmark located in Arau, the royal capital of Perlis, Malaysia.

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_69f348ddcbc48190950cabcc25ff29b3 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6aa7e50108190a70942725d12bb64 completed May 3, 2026, 1:53 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b84bf9ca08190b60c32846af2f23e completed June 12, 2026, 4:02 a.m.
NEDg Description generation batch_6a2b87330cf481909ca05de7eb516c05 completed June 12, 2026, 4:12 a.m.
NED2 Entity disambiguation (via description) batch_6a2b878fcb748190a8d2bb6bd2463381 completed June 12, 2026, 4:14 a.m.
Created at: April 30, 2026, 11:07 p.m.