Triple

T15822298
Position Surface form Disambiguated ID Type / Status
Subject Jackie E383641 entity
Predicate producer P490 FINISHED
Object Danja E346003 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: Danja | Statement: [Jackie, producer, Danja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danja
Context triple: [Jackie, producer, Danja]
  • A. Danja chosen
    Danja is an American record producer and songwriter known for his work on numerous pop and hip-hop hits alongside artists like Justin Timberlake and Nelly Furtado.
  • B. Dalva
    Dalva is a surname most notably associated with American film editor Robert Dalva, recognized for his work on major Hollywood productions.
  • C. Dalva
    Dalva is a 1988 novel by American author Jim Harrison that follows a middle-aged woman’s journey through memory, loss, and family history on the Great Plains.
  • D. Dunja
    Dunja is a feminine given name commonly used in South Slavic countries, often associated with the Bosnian human rights advocate Dunja Mijatović.
  • E. Thyra Danebod
    Thyra Danebod was a legendary Danish queen, celebrated in medieval sources as a wise and patriotic consort of King Gorm the Old and often credited with strengthening Denmark’s defenses.
  • 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_69d86da2858c819090cc8481e7207b6e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0c4a887d881908f74a1fcba390727 completed April 16, 2026, 11:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffa13392c48190b03cbed9df5a32a6 completed May 9, 2026, 9:03 p.m.
Created at: April 10, 2026, 4:49 a.m.