Triple

T36060337
Position Surface form Disambiguated ID Type / Status
Subject Ridley Scott filmography E1043060 entity
Predicate includesWork P2011 FINISHED
Object Legend
Legend is a 1985 dark fantasy film directed by Ridley Scott, known for its lush visual style, fairy-tale narrative, and Tim Curry’s iconic portrayal of the Lord of Darkness.
E198720 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: Legend | Statement: [Ridley Scott filmography, includesWork, Legend]
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: Legend
Triple: [Ridley Scott filmography, includesWork, Legend]
Generated description
Legend is a 1985 dark fantasy film directed by Ridley Scott, known for its lush visual style, fairy-tale narrative, and Tim Curry’s iconic portrayal of the Lord of Darkness.

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_69f76e2f09448190b0486d5ecad5e243 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7b1ecf4f481908505348a3ebe897b completed May 3, 2026, 8:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38cba75210819090607cf949aa519c completed June 22, 2026, 5:44 a.m.
NEDg Description generation batch_6a38cc3abea481908142bfac68c1f7ee completed June 22, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_6a38cd14a5f48190b924f3818ebdf8e7 completed June 22, 2026, 5:50 a.m.
Created at: May 3, 2026, 4:08 p.m.