Triple
T10008373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laugh Track |
E198307
|
entity |
| Predicate | hasSingle |
P3282
|
FINISHED |
| Object | Weird Goodbyes |
E834719
|
NE FINISHED |
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: Weird Goodbyes | Statement: [Laugh Track, hasSingle, Weird Goodbyes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weird Goodbyes Context triple: [Laugh Track, hasSingle, Weird Goodbyes]
-
A.
Weird Goodbyes
chosen
"Weird Goodbyes" is a song by The National featuring Bon Iver, known for its melancholic lyrics and atmospheric indie rock sound.
-
B.
Goodbyes
"Goodbyes" is a melancholic hip-hop/pop single by Post Malone featuring Young Thug, known for its themes of heartbreak and its commercial success on global music charts.
-
C.
Goodbyes
"Goodbyes" is a song by American singer Kelis from her 2006 album *Kelis Was Here*.
-
D.
Goodbye & Good Riddance
Goodbye & Good Riddance is the breakout studio album by American rapper and singer Juice WRLD, known for its emo-rap sound and hit singles like "Lucid Dreams."
-
E.
The Wrong Side of Goodbye
The Wrong Side of Goodbye is a crime novel by Michael Connelly featuring detective Harry Bosch working a cold missing-person case while serving as a part-time private investigator.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca830fcca48190bbbd9b20c233835f |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd38659c8190830d223edbfd74ec |
completed | April 2, 2026, 1:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d28209678c8190898d923753bb4472 |
completed | April 5, 2026, 3:38 p.m. |
Created at: March 30, 2026, 8:52 p.m.