Triple

T24017919
Position Surface form Disambiguated ID Type / Status
Subject Vittorio Nino Novarese E594734 entity
Predicate notableWork P4 FINISHED
Object The Egyptian (1954 film)
The Egyptian (1954 film) is an American epic historical drama set in ancient Egypt, adapted from Mika Waltari’s novel and noted for its lavish production design and exploration of religious and moral conflict.
E1614849 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: The Egyptian (1954 film) | Statement: [Vittorio Nino Novarese, notableWork, The Egyptian (1954 film)]
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: The Egyptian (1954 film)
Triple: [Vittorio Nino Novarese, notableWork, The Egyptian (1954 film)]
Generated description
The Egyptian (1954 film) is an American epic historical drama set in ancient Egypt, adapted from Mika Waltari’s novel and noted for its lavish production design and exploration of religious and moral conflict.

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_69e288be2c288190a3a46006945557f7 completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1d5a6123c8190871e10cb81dfa819 completed April 29, 2026, 9:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7ea4194c819095a542af335bcfe1 completed May 21, 2026, 9:52 p.m.
NEDg Description generation batch_6a0f7f6edf7081908ac1045c372e6351 completed May 21, 2026, 9:55 p.m.
NED2 Entity disambiguation (via description) batch_6a0f801bcc9c81908bbb270d7e762c11 completed May 21, 2026, 9:58 p.m.
Created at: April 17, 2026, 9:42 p.m.