Triple

T33043288

Position	Surface form	Disambiguated ID	Type / Status
Subject	Sultan Mahmud Al-Muktafi Billah Shah	`E845527`	entity
Predicate	child	`P120`	FINISHED
Object	Sultan Mizan Zainal Abidin Sultan Mizan Zainal Abidin is the Sultan of Terengganu and a former Yang di-Pertuan Agong (King) of Malaysia.	`E2287286`	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: Sultan Mizan Zainal Abidin | Statement: [Sultan Mahmud Al-Muktafi Billah Shah, child, Sultan Mizan Zainal Abidin]

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: Sultan Mizan Zainal Abidin
Triple: [Sultan Mahmud Al-Muktafi Billah Shah, child, Sultan Mizan Zainal Abidin]

Generated description

Sultan Mizan Zainal Abidin is the Sultan of Terengganu and a former Yang di-Pertuan Agong (King) of 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_69f3495242e48190996a2cb2beab5455`	completed	April 30, 2026, 12:21 p.m.
NER	Named-entity recognition	`batch_69f6d313424c8190b7c7ea6c79c62003`	completed	May 3, 2026, 4:46 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a477922f8b48190b7ef3fa1a57dff17`	completed	July 3, 2026, 8:56 a.m.
NEDg	Description generation	`batch_6a477b2a9a348190b6a624aa29e111d4`	completed	July 3, 2026, 9:04 a.m.
NED2	Entity disambiguation (via description)	`batch_6a477cdae220819095f1432350fd0111`	completed	July 3, 2026, 9:11 a.m.

Created at: May 1, 2026, 1:24 a.m.