Triple

T31151005
Position Surface form Disambiguated ID Type / Status
Subject Badr al-Din al-Ayni E794069 entity
Predicate notableWork P4 FINISHED
Object al-Binaya Sharh al-Hidaya
al-Binaya Sharh al-Hidaya is a major multi-volume Hanafi legal commentary by the Ottoman-era scholar Badr al-Din al-ʿAyni on the classic fiqh manual al-Hidaya.
 E1950546 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-Binaya Sharh al-Hidaya | Statement: [Badr al-Din al-Ayni, notableWork, al-Binaya Sharh al-Hidaya]
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-Binaya Sharh al-Hidaya
Triple: [Badr al-Din al-Ayni, notableWork, al-Binaya Sharh al-Hidaya]
Generated description
al-Binaya Sharh al-Hidaya is a major multi-volume Hanafi legal commentary by the Ottoman-era scholar Badr al-Din al-ʿAyni on the classic fiqh manual al-Hidaya.

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_69f224d41bb48190a5621cd1485e3a30 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f697efc9b88190b4b47643fc957d1d completed May 3, 2026, 12:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a294722d36c81909e1fd00d4379b8dc completed June 10, 2026, 11:14 a.m.
NEDg Description generation batch_6a294edd87888190a40f71d4d7f57b18 completed June 10, 2026, 11:47 a.m.
NED2 Entity disambiguation (via description) batch_6a2950ac30e88190a3f55d5a68f317d8 completed June 10, 2026, 11:55 a.m.
Created at: April 29, 2026, 9:06 p.m.