Triple
T7773406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glenn Miller |
E179127
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | In the Mood |
E529565
|
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: In the Mood | Statement: [Glenn Miller, notableWork, In the Mood]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: In the Mood Context triple: [Glenn Miller, notableWork, In the Mood]
-
A.
In the Mood
chosen
"In the Mood" is a famous big band-era jazz standard closely associated with Glenn Miller and widely recognized for its catchy swing rhythm and iconic saxophone riff.
-
B.
I'm in the Mood
"I'm in the Mood" is a classic blues song by John Lee Hooker, renowned for its hypnotic groove and influential role in postwar electric blues.
-
C.
Moody (My Love)
"Moody (My Love)" is a song featured on the album "Take My Time."
-
D.
In a Sentimental Mood
"In a Sentimental Mood" is a classic jazz standard composed by Duke Ellington, renowned for its lyrical melody and enduring popularity in the jazz repertoire.
-
E.
Tenderly
"Tenderly" is a popular jazz standard and romantic ballad that has been widely recorded by prominent jazz and pop artists.
- 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_69c69f30602c819082ab52cd4af5c592 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c70461b3e48190bf1e4d4f9e6bb08e |
completed | March 27, 2026, 10:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8c7ee407881908e591d216c504b24 |
completed | March 29, 2026, 6:34 a.m. |
Created at: March 27, 2026, 4:11 p.m.