Triple
T23447122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moodring |
E565567
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Fallen (remix) |
—
|
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: Fallen (remix) | Statement: [Moodring, hasPart, Fallen (remix)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fallen (remix) Context triple: [Moodring, hasPart, Fallen (remix)]
-
A.
Fallen (remix)
chosen
"Fallen (remix)" is a reworked version of the original track "Fallen," featuring altered production and arrangement to offer a fresh interpretation of the song.
-
B.
Fallen
"Fallen" is a melancholic pop ballad by Canadian singer-songwriter Sarah McLachlan, known for its introspective lyrics and emotive vocal performance.
-
C.
Fallen
Fallen is a 1998 supernatural crime thriller film known for its dark atmosphere and exploration of demonic possession, featuring cinematography by Newton Thomas Sigel.
-
D.
Fallen
"Fallen" is a notable single by the artist Afterglow, recognized as one of their standout tracks.
-
E.
Fallen
Fallen is a 2016 fantasy romance film, based on Lauren Kate’s novel, about a young woman sent to a mysterious reform school where she becomes entangled in a centuries-old conflict involving fallen angels.
- 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_69e24584f9488190bb32730bd2ce023e |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a649f7e8819080aeb120afd57aad |
completed | April 29, 2026, 6:33 a.m. |
Created at: April 17, 2026, 5:51 p.m.