Triple
T3319273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | For the Lovers |
E69753
|
entity |
| Predicate | writer |
P1360
|
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: [For the Lovers, writer, Danja]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Danja Context triple: [For the Lovers, writer, 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.
Kaja
Kaja is a diminutive or nickname commonly used for the given name Katarina.
-
C.
Neilia
Neilia was an American educator best known as the first wife of Joe Biden, who tragically died in a car accident in 1972 along with their infant daughter.
-
D.
Kara
Kara is a steel bracelet worn by Sikhs as a religious symbol of unity, restraint, and connection to the divine.
-
E.
Velda
Velda is the loyal and resourceful secretary and love interest of private investigator Mike Hammer in the hardboiled crime novel and film "Kiss Me Deadly."
- 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_69ad85a0bb048190a5458d2738012d61 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb1151f3c8190911af4edac701116 |
completed | March 8, 2026, 5:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b31a776f3881908e8b198f31921453 |
completed | March 12, 2026, 7:56 p.m. |
Created at: March 8, 2026, 3:11 p.m.