Triple
T17510224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All Good Things (Come to an End) |
E426429
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Danja |
—
|
NE NERFINISHED |
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: [All Good Things (Come to an End), producer, Danja]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Danja Context triple: [All Good Things (Come to an End), 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.
Danan
Danan is a town located in the Galguduud region of central Somalia.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4525b03c48190ada74a7da0f4739c |
completed | April 19, 2026, 3:56 a.m. |
Created at: April 10, 2026, 5:48 a.m.