Triple

T29483605
Position Surface form Disambiguated ID Type / Status
Subject سورة الصافات E747858 entity
Predicate تذكر قصة P84401 FINISHED
Object لوط عليه السلام
لوط عليه السلام هو نبي من أنبياء الله أُرسل إلى قومه لدعوتهم إلى التوحيد وترك الفواحش، وارتبطت سيرته بعذاب قومه الذين كذبوه.
E1868152 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: لوط عليه السلام | Statement: [سورة الصافات, تذكر قصة, لوط عليه السلام]
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: لوط عليه السلام
Triple: [سورة الصافات, تذكر قصة, لوط عليه السلام]
Generated description
لوط عليه السلام هو نبي من أنبياء الله أُرسل إلى قومه لدعوتهم إلى التوحيد وترك الفواحش، وارتبطت سيرته بعذاب قومه الذين كذبوه.

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_69f0bd43ba30819095eb1cfc3adf525c completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66bdbc7e88190a5fe93938d0cdc7c completed May 2, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25f12413a481909853d3e03d38bd5c completed June 7, 2026, 10:31 p.m.
NEDg Description generation batch_6a25f552f99881909b71511c1e143e8e completed June 7, 2026, 10:48 p.m.
NED2 Entity disambiguation (via description) batch_6a25f93080e48190b2aefc92165da88d completed June 7, 2026, 11:05 p.m.
Created at: April 28, 2026, 4:06 p.m.