Triple

T27227140
Position Surface form Disambiguated ID Type / Status
Subject Shia theology E682045 entity
Predicate historicalFigure P643 FINISHED
Object Allama al-Hilli
Allama al-Hilli was a prominent 13th–14th century Twelver Shia scholar, jurist, and theologian whose works significantly shaped Shia Islamic thought and law.
E1830001 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: Allama al-Hilli | Statement: [Shia theology, historicalFigure, Allama al-Hilli]
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: Allama al-Hilli
Triple: [Shia theology, historicalFigure, Allama al-Hilli]
Generated description
Allama al-Hilli was a prominent 13th–14th century Twelver Shia scholar, jurist, and theologian whose works significantly shaped Shia Islamic thought and law.

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_69eefacdad7881908b7bca61c90a1a1e completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f6264bcdc08190b0860b3015aac6c6 completed May 2, 2026, 4:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1ccf0b77c48190b66e905f1ddc56d3 completed June 1, 2026, 12:15 a.m.
NEDg Description generation batch_6a1ccf8456c8819096402635e1399ba4 completed June 1, 2026, 12:17 a.m.
NED2 Entity disambiguation (via description) batch_6a249457116881909199d0b381a902c3 completed June 6, 2026, 9:42 p.m.
Created at: April 27, 2026, 9:44 a.m.