Triple

T23867961
Position Surface form Disambiguated ID Type / Status
Subject Winter of Discontent E592639 entity
Predicate director P255 FINISHED
Object Ibrahim El-Batout
Ibrahim El-Batout is an Egyptian filmmaker and former war cameraman known for his independent, socially engaged films that often explore political and human rights issues in contemporary Egypt.
E1804241 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: Ibrahim El-Batout | Statement: [Winter of Discontent, director, Ibrahim El-Batout]
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: Ibrahim El-Batout
Triple: [Winter of Discontent, director, Ibrahim El-Batout]
Generated description
Ibrahim El-Batout is an Egyptian filmmaker and former war cameraman known for his independent, socially engaged films that often explore political and human rights issues in contemporary Egypt.

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_69e25d23a5c88190ae3999c70ca15e08 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1cae548dc8190a5f84f2cd7f9778e completed April 29, 2026, 9:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a15d76a3c6c819094455069fdee5547 completed May 26, 2026, 5:24 p.m.
NEDg Description generation batch_6a15d82ac0fc819082a575f3f11f25da completed May 26, 2026, 5:28 p.m.
NED2 Entity disambiguation (via description) batch_6a15d8e229e88190aaf00c672b1bf5da completed May 26, 2026, 5:31 p.m.
Created at: April 17, 2026, 8:14 p.m.