Triple

T25005767
Position Surface form Disambiguated ID Type / Status
Subject Dave McKean E625836 entity
Predicate directedFilm P13455 FINISHED
Object The Gospel of Us
The Gospel of Us is a 2012 British art-house film adaptation of the Passion story, visually stylized and reimagined from the Port Talbot Passion play.
 E1658712 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 Gospel of Us | Statement: [Dave McKean, directedFilm, The Gospel of Us]
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 Gospel of Us
Triple: [Dave McKean, directedFilm, The Gospel of Us]
Generated description
The Gospel of Us is a 2012 British art-house film adaptation of the Passion story, visually stylized and reimagined from the Port Talbot Passion play.

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_69e2ff26c50481908bc82e799c9e6587 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f44b113f8c8190ae05102e9c2ae076 completed May 1, 2026, 6:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1033730f0881908da32ad0591e7f8f completed May 22, 2026, 10:44 a.m.
NEDg Description generation batch_6a103422072c8190949546db07c0b9bd completed May 22, 2026, 10:46 a.m.
NED2 Entity disambiguation (via description) batch_6a103522b834819090aec1df37f496e8 completed May 22, 2026, 10:51 a.m.
Created at: April 18, 2026, 6:05 a.m.