Triple
T13733314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hard Candy |
E329865
|
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: [Hard Candy, producer, Danja]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Danja Context triple: [Hard Candy, 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.
Dunja
Dunja is a feminine given name commonly used in South Slavic countries, often associated with the Bosnian human rights advocate Dunja Mijatović.
-
D.
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.
-
E.
Kaja
Kaja is a diminutive or nickname commonly used for the given name Katarina.
- 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_69d80772315881908f980cae40d91664 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69de0201d3c48190aa306be231a28bc1 |
completed | April 14, 2026, 8:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d66cb088190be2621753d0a6740 |
completed | May 3, 2026, 7:09 p.m. |
Created at: April 9, 2026, 9:55 p.m.