Triple
T22013409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bill Schneider |
E543639
|
entity |
| Predicate | memberOf |
P10
|
FINISHED |
| Object | The Love Songs |
—
|
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: The Love Songs | Statement: [Bill Schneider, memberOf, The Love Songs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Love Songs Context triple: [Bill Schneider, memberOf, The Love Songs]
-
A.
The Love Songs
chosen
The Love Songs is a musical group known for featuring musician Bill Schneider among its members.
-
B.
Songs of Love
"Songs of Love" is a track by the American rock band Blondie from their 2003 studio album "The Curse of Blondie."
-
C.
Strings of Love
"Strings of Love" is a song by the alternative rock band Ghost of a Dog.
-
D.
Love in Song
"Love in Song" is a melancholic, orchestral-tinged track by Paul McCartney and Wings from their 1975 album *Venus and Mars*.
-
E.
A Love Song
A Love Song is a 2022 independent romantic drama film starring Dale Dickey as a solitary widow awaiting the arrival of a long-lost flame at a remote lakeside campsite.
- 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_69e11e2db934819095556760c7d85e4d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127a5e624819082ed5beeb4bc82fa |
completed | April 28, 2026, 9:33 p.m. |
Created at: April 16, 2026, 8:22 p.m.