Triple
T19584021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bringing Down the Horse |
E490064
|
entity |
| Predicate | includesHitSingle |
P15293
|
FINISHED |
| Object | Three Marlenas |
—
|
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: Three Marlenas | Statement: [Bringing Down the Horse, includesHitSingle, Three Marlenas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Three Marlenas Context triple: [Bringing Down the Horse, includesHitSingle, Three Marlenas]
-
A.
Three Marlenas
chosen
"Three Marlenas" is a rock song by American band The Wallflowers, known as one of the standout tracks from their acclaimed 1996 album "Bringing Down the Horse."
-
B.
The Blue Nun
The Blue Nun is a track by the Beastie Boys from their genre-blending 1992 album "Check Your Head."
-
C.
Goodbye Marie
"Goodbye Marie" is a country song recorded by Kenny Rogers about a bittersweet farewell to a lover.
-
D.
La Malène
La Malène is a small picturesque village in southern France, known as a gateway to the scenic Gorges du Tarn and popular for river-based outdoor activities.
-
E.
Milena
Milena is the birth name of actress Mila Kunis, a Ukrainian-born American performer known for roles in "That '70s Show" and "Black Swan."
- 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e64050127c8190b93b8716a1a4ad81 |
completed | April 20, 2026, 3:03 p.m. |
Created at: April 10, 2026, 1:42 p.m.