Triple
T8116377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Very |
E189483
|
entity |
| Predicate | containsTrack |
P3284
|
FINISHED |
| Object | One in a Million |
E341634
|
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: One in a Million | Statement: [Very, containsTrack, One in a Million]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: One in a Million Context triple: [Very, containsTrack, One in a Million]
-
A.
One in a Million
chosen
"One in a Million" is Aaliyah's influential 1996 R&B album that helped redefine the genre with its innovative production and smooth, futuristic sound.
-
B.
One in a Million
"One in a Million" is an R&B song by American singer-songwriter Ne-Yo, known for its smooth production and romantic lyrics.
-
C.
A Million to One
"A Million to One" is a doo-wop ballad best known for its romantic, pleading lyrics and classic 1960s vocal harmony style.
-
D.
A Million Love Songs
"A Million Love Songs" is a romantic pop ballad by British boy band Take That, released in 1992 and known for its soulful melody and heartfelt lyrics.
-
E.
A Billion
"A Billion" is a song featured on the soundtrack of the musical film "The King & I."
- 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_69ca82baad008190ab2859712b9b1607 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb43320bf881909f97a235451bb3a4 |
completed | March 31, 2026, 3:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc944439488190b95788e3a77ee732 |
completed | April 1, 2026, 3:43 a.m. |
Created at: March 30, 2026, 5:33 p.m.