Triple

T33364058
Position Surface form Disambiguated ID Type / Status
Subject Ahmad ibn Shuʿayb al-Nasaʾi E854302 entity
Predicate birthPlace P1 FINISHED
Object Nasa, Khurasan
Nasa, Khurasan was a historic town in the Khurasan region of northeastern Iran, known as the birthplace of the prominent hadith scholar Ahmad ibn Shuʿayb al-Nasaʾi.
E2048400 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: Nasa, Khurasan | Statement: [Ahmad ibn Shuʿayb al-Nasaʾi, birthPlace, Nasa, Khurasan]
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: Nasa, Khurasan
Triple: [Ahmad ibn Shuʿayb al-Nasaʾi, birthPlace, Nasa, Khurasan]
Generated description
Nasa, Khurasan was a historic town in the Khurasan region of northeastern Iran, known as the birthplace of the prominent hadith scholar Ahmad ibn Shuʿayb al-Nasaʾi.

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_69f3496bda8c8190bfc8fade9d1b791c completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6dfce57d081908316e0c42dc217eb completed May 3, 2026, 5:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a355216c83c819084f1382fefff9375 completed June 19, 2026, 2:28 p.m.
NEDg Description generation batch_6a355452f8548190b39291449f7621eb completed June 19, 2026, 2:38 p.m.
NED2 Entity disambiguation (via description) batch_6a3554f13e008190ae2405c26c992ce9 completed June 19, 2026, 2:40 p.m.
Created at: May 1, 2026, 1:34 a.m.