Triple

T35999229
Position Surface form Disambiguated ID Type / Status
Subject Al-Shahid al-Awwal E1041081 entity
Predicate notableWork P4 FINISHED
Object al-Durus al-Sharʿiyya
al-Durus al-Sharʿiyya is a foundational Shi'a Islamic jurisprudence textbook by the 14th-century scholar Al-Shahid al-Awwal, widely studied in traditional seminaries.
 E2165188 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: al-Durus al-Sharʿiyya | Statement: [Al-Shahid al-Awwal, notableWork, al-Durus al-Sharʿiyya]
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: al-Durus al-Sharʿiyya
Triple: [Al-Shahid al-Awwal, notableWork, al-Durus al-Sharʿiyya]
Generated description
al-Durus al-Sharʿiyya is a foundational Shi'a Islamic jurisprudence textbook by the 14th-century scholar Al-Shahid al-Awwal, widely studied in traditional seminaries.

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_69f76e29084c819083987b828d414de7 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7ac8118148190bef390a078185205 completed May 3, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38bfefcd6481909c56d9b41f247993 completed June 22, 2026, 4:54 a.m.
NEDg Description generation batch_6a38c0d82d0c81908f70877d80b439a9 completed June 22, 2026, 4:58 a.m.
NED2 Entity disambiguation (via description) batch_6a38c14a3b6c81908d6bcb4ed8316a28 completed June 22, 2026, 4:59 a.m.
Created at: May 3, 2026, 4:07 p.m.