Triple

T33858427
Position Surface form Disambiguated ID Type / Status
Subject House of Terengganu E867852 entity
Predicate usesTitle P10405 FINISHED
Object Yang di-Pertuan Muda
Yang di-Pertuan Muda is a royal title historically used in Malay sultanates, notably associated with junior or heir-apparent rulers within certain royal houses.
E2076153 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: Yang di-Pertuan Muda | Statement: [House of Terengganu, usesTitle, Yang di-Pertuan Muda]
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: Yang di-Pertuan Muda
Triple: [House of Terengganu, usesTitle, Yang di-Pertuan Muda]
Generated description
Yang di-Pertuan Muda is a royal title historically used in Malay sultanates, notably associated with junior or heir-apparent rulers within certain royal houses.

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_69f349943ccc8190a3c41a3e0ae46cbf completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f7007970ac819092f5ab972587afd3 completed May 3, 2026, 7:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3689c39d7481908a5d5fd908326294 completed June 20, 2026, 12:38 p.m.
NEDg Description generation batch_6a368d972f4c81909b4e5e4bd034b264 completed June 20, 2026, 12:54 p.m.
NED2 Entity disambiguation (via description) batch_6a368e2093b88190a09398f5e3fa664f completed June 20, 2026, 12:57 p.m.
Created at: May 1, 2026, 1:47 a.m.