Triple
T18085028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Threads |
E432809
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Redemption Day |
—
|
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: Redemption Day | Statement: [Threads, hasTrack, Redemption Day]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Redemption Day Context triple: [Threads, hasTrack, Redemption Day]
-
A.
Redemption Day
chosen
"Redemption Day" is a politically charged folk-rock song by Sheryl Crow reflecting on war, justice, and human conscience.
-
B.
Redemption
Redemption is a Star Wars: Tales of the Jedi comic miniseries that follows the aftermath of the Great Sith War and the quest for atonement by fallen Jedi Ulic Qel-Droma.
-
C.
Redemption
Redemption is the profound moral and spiritual transformation in which a flawed or fallen individual seeks and attains forgiveness, renewal, and a chance to reclaim their humanity.
-
D.
Redemption
Redemption is a fictional town that serves as the central backdrop for the events and characters in the story "The Lady."
-
E.
Redemption
Redemption is a 2013 British action drama film starring Jason Statham as a troubled ex-soldier seeking atonement on the streets of London.
- 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_69d8b907d05c819083cc3bd6021089e6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4d9fdb00c8190b4769699e94c8941 |
completed | April 19, 2026, 1:34 p.m. |
Created at: April 10, 2026, 10:27 a.m.