Triple

T25843580
Position Surface form Disambiguated ID Type / Status
Subject سورة الأعراف E651002 entity
Predicate تذكر قصة P84401 FINISHED
Object نوح عليه السلام
نوح عليه السلام هو نبي من أولي العزم أرسله الله إلى قومه للدعوة إلى التوحيد، واشتهر بقصة السفينة والنجاة من الطوفان العظيم.
E1700146 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: نوح عليه السلام | Statement: [سورة الأعراف, تذكر قصة, نوح 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: نوح عليه السلام
Triple: [سورة الأعراف, تذكر قصة, نوح عليه السلام]
Generated description
نوح عليه السلام هو نبي من أولي العزم أرسله الله إلى قومه للدعوة إلى التوحيد، واشتهر بقصة السفينة والنجاة من الطوفان العظيم.

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_69e7ab38086081908f3a8e7e0c6efd83 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f6023662a48190b8eb77eebc225c36 completed May 2, 2026, 1:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ecaba278819082aab64b83f20704 completed May 22, 2026, 11:54 p.m.
NEDg Description generation batch_6a10ed930a148190b794107b779bbdfd completed May 22, 2026, 11:58 p.m.
NED2 Entity disambiguation (via description) batch_6a10efcd4df481908ec1f756b7115d2a completed May 23, 2026, 12:07 a.m.
Created at: April 22, 2026, 7:51 a.m.