Triple
T19584864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One Hot Minute |
E490082
|
entity |
| Predicate | track |
P17929
|
FINISHED |
| Object | Tearjerker |
—
|
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: Tearjerker | Statement: [One Hot Minute, track, Tearjerker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tearjerker Context triple: [One Hot Minute, track, Tearjerker]
-
A.
Tearjerker
chosen
"Tearjerker" is a melancholic, emotionally charged song by the Red Hot Chili Peppers from their 1995 album *One Hot Minute*.
-
B.
So Emotional
"So Emotional" is a 1987 dance-pop song by Whitney Houston that became one of her number-one hits on the Billboard Hot 100.
-
C.
Tears
"Tears" is a 1937 jazz composition co-written and recorded by pioneering gypsy jazz guitarist Django Reinhardt, known for its lyrical melody and prominent place in his repertoire.
-
D.
TEAR
TEAR is the abbreviation for the Spanish Navy’s Tercio de Armada, an elite marine infantry force specializing in amphibious and expeditionary operations.
-
E.
Tears of Joy
"Tears of Joy" is a song featured on the album "Fruit at the Bottom" by the musical duo Wendy & Lisa.
- 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e64050127c8190b93b8716a1a4ad81 |
completed | April 20, 2026, 3:03 p.m. |
Created at: April 10, 2026, 1:42 p.m.