Triple
T21440611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Endangered Species |
E528929
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Am I Losin' |
—
|
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: Am I Losin' | Statement: [Endangered Species, hasTrack, Am I Losin']
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Am I Losin' Context triple: [Endangered Species, hasTrack, Am I Losin']
-
A.
Am I Losin'?
chosen
"Am I Losin'?" is a song by Southern rock band Lynyrd Skynyrd from their 1975 album *Nuthin' Fancy*.
-
B.
Losing It
"Losing It" is a popular song by Canadian country duo R. City that showcases their blend of Caribbean-influenced pop and contemporary R&B.
-
C.
Losing It All
"Losing It All" is a song by the American metalcore band Lowborn.
-
D.
You Lost Me
"You Lost Me" is a soulful pop ballad by Christina Aguilera from her 2010 album *Bionic*, noted for its emotional vocals and themes of heartbreak and betrayal.
-
E.
Like I'm Gonna Lose You
"Like I'm Gonna Lose You" is a soulful pop ballad by Meghan Trainor featuring John Legend that reflects on cherishing loved ones as if every moment with them could be the last.
- 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_69e0c4569fa081908101baa24f8745db |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b70101208190a77bf5dd53dce37a |
completed | April 22, 2026, 11:54 a.m. |
Created at: April 16, 2026, 6:05 p.m.