Triple
T21563979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Eyes |
E532114
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Green Eyes, Part 3 |
—
|
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, Part 3 | Statement: [Green Eyes, hasPart, Green Eyes, Part 3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Green Eyes, Part 3 Context triple: [Green Eyes, hasPart, Green Eyes, Part 3]
-
A.
Big Green Eyes
"Big Green Eyes" is a track by the folk singer-songwriter Freight Train.
-
B.
Girl with Green Eyes
Girl with Green Eyes is a 1964 British drama film, adapted from Edna O’Brien’s novel, about a shy Irish country girl’s complicated romance in Dublin.
-
C.
Green Eyes
"Green Eyes" is a song by the American rock band Joseph, known for its emotive harmonies and introspective indie-folk style.
-
D.
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.
-
E.
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.
- 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_69e0c460db088190828c64206a450273 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eed2e6c19c81909eaae408d94f0625 |
completed | April 27, 2026, 3:07 a.m. |
Created at: April 16, 2026, 6:30 p.m.