Triple
T20699938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Z-Cars |
E508751
|
entity |
| Predicate | spinOff |
P7736
|
FINISHED |
| Object | Softly, Softly: Taskforce |
—
|
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: Softly, Softly: Taskforce | Statement: [Z-Cars, spinOff, Softly, Softly: Taskforce]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Softly, Softly: Taskforce Context triple: [Z-Cars, spinOff, Softly, Softly: Taskforce]
-
A.
Softly
Softly is a song featured on the album "Blush."
-
B.
Softly, Softly
chosen
Softly, Softly is a British police procedural television series from the 1960s that followed regional crime squads and became well known for its realistic depiction of police work.
-
C.
Softly and Tenderly
"Softly and Tenderly" is a classic Christian hymn, often sung as an invitation song, known for its gentle melody and themes of Jesus calling believers to come home.
-
D.
Love So Soft
"Love So Soft" is a soulful pop single by American singer Kelly Clarkson, known for its powerful vocals and retro-inspired production.
-
E.
A Certain Softness
"A Certain Softness" is a gentle, bossa nova–influenced love song by Paul McCartney, noted for its intimate acoustic arrangement and romantic lyrics.
- 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_69e0b4c2b2a481909e31e9cb8f81ab55 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6c18a77308190b7c2517d82a145cd |
completed | April 21, 2026, 12:15 a.m. |
Created at: April 16, 2026, 12:12 p.m.