Triple

T7714661
Position Surface form Disambiguated ID Type / Status
Subject The Dark Tower (2017 film) E174850 entity
Predicate screenwriter P2831 FINISHED
Object Nikolaj Arcel E683363 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: Nikolaj Arcel | Statement: [The Dark Tower (2017 film), screenwriter, Nikolaj Arcel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nikolaj Arcel
Context triple: [The Dark Tower (2017 film), screenwriter, Nikolaj Arcel]
  • A. Nikolaj Arcel chosen
    Nikolaj Arcel is a Danish filmmaker and screenwriter known for directing films such as "A Royal Affair" and the adaptation of Stephen King's "The Dark Tower."
  • B. Nicolaj Monberg
    Nicolaj Monberg is a film editor known for his work on the action thriller "Cold Pursuit."
  • C. Nikolaj Lie Kaas
    Nikolaj Lie Kaas is a Danish actor known for his versatile performances in both Scandinavian cinema and international films.
  • D. Nikolaj Malchow-Møller
    Nikolaj Malchow-Møller is a Danish economist and academic leader who serves as the rector of Copenhagen Business School.
  • E. Fredrik Meltzer
    Fredrik Meltzer was a Norwegian politician and merchant best known for creating the design of Norway’s national flag in the early 19th century.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c6995c463c8190a14458036249d419 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c702ca8f048190a6ea27b8cee2f93e completed March 27, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8b508fa2081908ed05ca8c4815249 completed March 29, 2026, 5:13 a.m.
Created at: March 27, 2026, 4:04 p.m.