Triple

T25190187
Position Surface form Disambiguated ID Type / Status
Subject Reykjavík-Rotterdam E630845 entity
Predicate director P255 FINISHED
Object Óskar Jónasson
Óskar Jónasson is an Icelandic film director best known internationally for his crime thriller "Reykjavík-Rotterdam," which inspired the Hollywood remake "Contraband."
E1677847 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: Óskar Jónasson | Statement: [Reykjavík-Rotterdam, director, Óskar Jónasson]
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: Óskar Jónasson
Triple: [Reykjavík-Rotterdam, director, Óskar Jónasson]
Generated description
Óskar Jónasson is an Icelandic film director best known internationally for his crime thriller "Reykjavík-Rotterdam," which inspired the Hollywood remake "Contraband."

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_69e75a8a6d088190ba1e82a4345225e7 completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f46e0dc9908190b2d957d9c6314cfc completed May 1, 2026, 9:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1075c76bb48190b88f52f758d8f1ac completed May 22, 2026, 3:27 p.m.
NEDg Description generation batch_6a1079d95d1c819093e5780a2f3c1532 completed May 22, 2026, 3:44 p.m.
NED2 Entity disambiguation (via description) batch_6a107a9277848190b817ac608347ad3e completed May 22, 2026, 3:47 p.m.
Created at: April 21, 2026, 12:44 p.m.