Triple
T19859292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Boatman’s Call |
E477213
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Green Eyes |
—
|
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: Green Eyes | Statement: [The Boatman’s Call, hasTrack, Green Eyes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Green Eyes Context triple: [The Boatman’s Call, hasTrack, Green Eyes]
-
A.
Green Eyes
"Green Eyes" is a song by the American rock band Joseph, known for its emotive harmonies and introspective indie-folk style.
-
B.
Green Eyes
chosen
"Green Eyes" is a soulful, jazz-inflected R&B song by Erykah Badu from her acclaimed album *Mama’s Gun*, noted for its emotional vulnerability and evolving three-part structure.
-
C.
Violet Eyes
Violet Eyes is a celebrity-branded fragrance from House of Taylor, inspired by and named in honor of Elizabeth Taylor’s iconic violet-colored eyes.
-
D.
Blue Eye
Blue Eye is a strikingly clear, blue-colored natural spring and popular tourist attraction in southern Albania, famed for its deep, eye-like appearance and surrounding lush scenery.
-
E.
Big Green Eyes
"Big Green Eyes" is a track by the folk singer-songwriter Freight Train.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6586e8b648190bb650d7f2816dda1 |
completed | April 20, 2026, 4:46 p.m. |
Created at: April 10, 2026, 1:51 p.m.