Triple

T36552470
Position Surface form Disambiguated ID Type / Status
Subject A Girl Walks Home Alone at Night E901306 entity
Predicate starring P1507 FINISHED
Object Arash Marandi
Arash Marandi is an Iranian-German actor best known internationally for his role in the acclaimed Iranian vampire western film "A Girl Walks Home Alone at Night."
E2191637 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: Arash Marandi | Statement: [A Girl Walks Home Alone at Night, starring, Arash Marandi]
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: Arash Marandi
Triple: [A Girl Walks Home Alone at Night, starring, Arash Marandi]
Generated description
Arash Marandi is an Iranian-German actor best known internationally for his role in the acclaimed Iranian vampire western film "A Girl Walks Home Alone at Night."

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_69f76e61217081908b79d610fe67b013 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c26059348190bfdd8bb0f6b7074d completed May 3, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3a094ddad08190ae31aced244f48ff completed June 23, 2026, 4:19 a.m.
NEDg Description generation batch_6a3a0adedd848190884ffeb782d98cdc completed June 23, 2026, 4:26 a.m.
NED2 Entity disambiguation (via description) batch_6a3a0bf00df48190bc1a4333516a7009 completed June 23, 2026, 4:30 a.m.
Created at: May 3, 2026, 4:11 p.m.